From 2d326739f9b3f964424f47a61026c3d15fe7bc43 Mon Sep 17 00:00:00 2001
From: ehatzi <ehatzi@iti.gr>
Date: Fri, 25 Nov 2016 14:51:22 +0200
Subject: [PATCH 1/3] Added documentation

---
 .../@AggregatorBase/AggregatorBase.m          |  20 +
 .../@ClassifierBase/ClassifierBase.m          |  29 +-
 .../+experiment/@Experimenter/Experimenter.m  |  14 +-
 .../FeatureExtractionBase.m                   |  18 +
 .../FeatureSelectionBase.m                    |  19 +-
 .../@PreprocessingBase/PreprocessingBase.m    |  17 +
 +eegtoolkit/+util/@InstanceSet/InstanceSet.m  |  58 +-
 +eegtoolkit/+util/@Session/Session.m          |  33 +-
 +eegtoolkit/+util/@Trial/Trial.m              |  17 +-
 .../@AggregatorBase/AggregatorBase.html       | 101 +++
 .../@AggregatorBase/AggregatorBase.m          |  35 ++
 .../+aggregation/@AggregatorBase/graph.dot    |   6 +
 .../+aggregation/@AggregatorBase/graph.html   |  28 +
 .../+aggregation/@AggregatorBase/graph.map    |   1 +
 .../+aggregation/@AggregatorBase/graph.png    | Bin 0 -> 5615 bytes
 .../+aggregation/@AggregatorBase/index.html   |  32 +
 .../@ChannelAveraging/ChannelAveraging.html   |  83 +++
 .../@ChannelAveraging/ChannelAveraging.m      |  33 +
 .../+aggregation/@ChannelAveraging/graph.dot  |   6 +
 .../+aggregation/@ChannelAveraging/graph.html |  28 +
 .../+aggregation/@ChannelAveraging/graph.map  |   1 +
 .../+aggregation/@ChannelAveraging/graph.png  | Bin 0 -> 6156 bytes
 .../+aggregation/@ChannelAveraging/index.html |  32 +
 .../@ChannelConcat/ChannelConcat.html         |  84 +++
 .../@ChannelConcat/ChannelConcat.m            |  34 +
 .../+aggregation/@ChannelConcat/graph.dot     |   6 +
 .../+aggregation/@ChannelConcat/graph.html    |  28 +
 .../+aggregation/@ChannelConcat/graph.map     |   1 +
 .../+aggregation/@ChannelConcat/graph.png     | Bin 0 -> 5232 bytes
 .../+aggregation/@ChannelConcat/index.html    |  32 +
 .../@ChannelRatio/ChannelRatio.html           |  83 +++
 .../+aggregation/@ChannelRatio/ChannelRatio.m |  33 +
 .../+aggregation/@ChannelRatio/graph.dot      |   6 +
 .../+aggregation/@ChannelRatio/graph.html     |  28 +
 .../+aggregation/@ChannelRatio/graph.map      |   1 +
 .../+aggregation/@ChannelRatio/graph.png      | Bin 0 -> 5235 bytes
 .../+aggregation/@ChannelRatio/index.html     |  32 +
 .../+aggregation/@Fisher/Fisher.html          | 147 +++++
 doc/+eegtoolkit/+aggregation/@Fisher/Fisher.m |  97 +++
 .../+aggregation/@Fisher/graph.dot            |   6 +
 .../+aggregation/@Fisher/graph.html           |  28 +
 .../+aggregation/@Fisher/graph.map            |   1 +
 .../+aggregation/@Fisher/graph.png            | Bin 0 -> 3685 bytes
 .../+aggregation/@Fisher/index.html           |  32 +
 .../+aggregation/@LateFusion/LateFusion.html  |  81 +++
 .../+aggregation/@LateFusion/LateFusion.m     |  31 +
 .../+aggregation/@LateFusion/graph.dot        |   6 +
 .../+aggregation/@LateFusion/graph.html       |  28 +
 .../+aggregation/@LateFusion/graph.map        |   1 +
 .../+aggregation/@LateFusion/graph.png        | Bin 0 -> 4775 bytes
 .../+aggregation/@LateFusion/index.html       |  32 +
 doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html  | 133 ++++
 doc/+eegtoolkit/+aggregation/@VLAD/VLAD.m     |  83 +++
 doc/+eegtoolkit/+aggregation/@VLAD/graph.dot  |   6 +
 doc/+eegtoolkit/+aggregation/@VLAD/graph.html |  28 +
 doc/+eegtoolkit/+aggregation/@VLAD/graph.map  |   1 +
 doc/+eegtoolkit/+aggregation/@VLAD/graph.png  | Bin 0 -> 3831 bytes
 doc/+eegtoolkit/+aggregation/@VLAD/index.html |  32 +
 .../+classification/@Adaboost/Adaboost.html   | 181 ++++++
 .../+classification/@Adaboost/Adaboost.m      | 131 ++++
 .../+classification/@Adaboost/graph.dot       |   6 +
 .../+classification/@Adaboost/graph.html      |  28 +
 .../+classification/@Adaboost/graph.map       |   1 +
 .../+classification/@Adaboost/graph.png       | Bin 0 -> 4358 bytes
 .../+classification/@Adaboost/index.html      |  32 +
 .../@CSPWrapper/CSPWrapper.html               | 183 ++++++
 .../+classification/@CSPWrapper/CSPWrapper.m  | 133 ++++
 .../+classification/@CSPWrapper/graph.dot     |   6 +
 .../+classification/@CSPWrapper/graph.html    |  28 +
 .../+classification/@CSPWrapper/graph.map     |   1 +
 .../+classification/@CSPWrapper/graph.png     | Bin 0 -> 5343 bytes
 .../+classification/@CSPWrapper/index.html    |  32 +
 .../@ClassifierBase/ClassifierBase.html       | 115 ++++
 .../@ClassifierBase/ClassifierBase.m          |  42 ++
 .../+classification/@ClassifierBase/graph.dot |   6 +
 .../@ClassifierBase/graph.html                |  28 +
 .../+classification/@ClassifierBase/graph.map |   1 +
 .../+classification/@ClassifierBase/graph.png | Bin 0 -> 5275 bytes
 .../@ClassifierBase/index.html                |  32 +
 .../+classification/@CombiCCA/CombiCCA.html   | 223 +++++++
 .../+classification/@CombiCCA/CombiCCA.m      | 173 +++++
 .../+classification/@CombiCCA/graph.dot       |   6 +
 .../+classification/@CombiCCA/graph.html      |  28 +
 .../+classification/@CombiCCA/graph.map       |   1 +
 .../+classification/@CombiCCA/graph.png       | Bin 0 -> 4664 bytes
 .../+classification/@CombiCCA/index.html      |  32 +
 .../FusionClassifierWrapper.html              | 121 ++++
 .../FusionClassifierWrapper.m                 |  71 +++
 .../@FusionClassifierWrapper/graph.dot        |   6 +
 .../@FusionClassifierWrapper/graph.html       |  28 +
 .../@FusionClassifierWrapper/graph.map        |   1 +
 .../@FusionClassifierWrapper/graph.png        | Bin 0 -> 7050 bytes
 .../@FusionClassifierWrapper/index.html       |  32 +
 .../+classification/@ITCCA/ITCCA.html         | 256 ++++++++
 .../+classification/@ITCCA/ITCCA.m            | 206 ++++++
 .../+classification/@ITCCA/graph.dot          |   6 +
 .../+classification/@ITCCA/graph.html         |  28 +
 .../+classification/@ITCCA/graph.map          |   1 +
 .../+classification/@ITCCA/graph.png          | Bin 0 -> 3828 bytes
 .../+classification/@ITCCA/index.html         |  32 +
 .../+classification/@L1MCCA/L1MCCA.html       | 289 +++++++++
 .../+classification/@L1MCCA/L1MCCA.m          | 239 +++++++
 .../+classification/@L1MCCA/graph.dot         |   6 +
 .../+classification/@L1MCCA/graph.html        |  28 +
 .../+classification/@L1MCCA/graph.map         |   1 +
 .../+classification/@L1MCCA/graph.png         | Bin 0 -> 4313 bytes
 .../+classification/@L1MCCA/index.html        |  32 +
 doc/+eegtoolkit/+classification/@LDA/LDA.html | 131 ++++
 doc/+eegtoolkit/+classification/@LDA/LDA.m    |  81 +++
 .../+classification/@LDA/graph.dot            |   6 +
 .../+classification/@LDA/graph.html           |  28 +
 .../+classification/@LDA/graph.map            |   1 +
 .../+classification/@LDA/graph.png            | Bin 0 -> 3410 bytes
 .../+classification/@LDA/index.html           |  32 +
 .../+classification/@LIBSVM/LIBSVM.html       | 166 +++++
 .../+classification/@LIBSVM/LIBSVM.m          | 114 ++++
 .../+classification/@LIBSVM/graph.dot         |   6 +
 .../+classification/@LIBSVM/graph.html        |  28 +
 .../+classification/@LIBSVM/graph.map         |   1 +
 .../+classification/@LIBSVM/graph.png         | Bin 0 -> 4367 bytes
 .../+classification/@LIBSVM/index.html        |  32 +
 .../@LIBSVMFast/LIBSVMFast.html               | 174 ++++++
 .../+classification/@LIBSVMFast/LIBSVMFast.m  | 124 ++++
 .../+classification/@LIBSVMFast/graph.dot     |   6 +
 .../+classification/@LIBSVMFast/graph.html    |  28 +
 .../+classification/@LIBSVMFast/graph.map     |   1 +
 .../+classification/@LIBSVMFast/graph.png     | Bin 0 -> 5360 bytes
 .../+classification/@LIBSVMFast/index.html    |  32 +
 .../+classification/@MLDA/MLDA.html           | 183 ++++++
 doc/+eegtoolkit/+classification/@MLDA/MLDA.m  | 133 ++++
 .../+classification/@MLDA/graph.dot           |   6 +
 .../+classification/@MLDA/graph.html          |  28 +
 .../+classification/@MLDA/graph.map           |   1 +
 .../+classification/@MLDA/graph.png           | Bin 0 -> 3961 bytes
 .../+classification/@MLDA/index.html          |  32 +
 doc/+eegtoolkit/+classification/@MLR/MLR.html | 165 +++++
 doc/+eegtoolkit/+classification/@MLR/MLR.m    | 115 ++++
 .../+classification/@MLR/graph.dot            |   6 +
 .../+classification/@MLR/graph.html           |  28 +
 .../+classification/@MLR/graph.map            |   1 +
 .../+classification/@MLR/graph.png            | Bin 0 -> 3476 bytes
 .../+classification/@MLR/index.html           |  32 +
 .../+classification/@MLTREE/MLTREE.html       | 190 ++++++
 .../+classification/@MLTREE/MLTREE.m          | 140 +++++
 .../+classification/@MLTREE/graph.dot         |   6 +
 .../+classification/@MLTREE/graph.html        |  28 +
 .../+classification/@MLTREE/graph.map         |   1 +
 .../+classification/@MLTREE/graph.png         | Bin 0 -> 4287 bytes
 .../+classification/@MLTREE/index.html        |  32 +
 .../@MLTboxMulticlass/MLTboxMulticlass.html   | 154 +++++
 .../@MLTboxMulticlass/MLTboxMulticlass.m      | 104 ++++
 .../@MLTboxMulticlass/graph.dot               |   6 +
 .../@MLTboxMulticlass/graph.html              |  28 +
 .../@MLTboxMulticlass/graph.map               |   1 +
 .../@MLTboxMulticlass/graph.png               | Bin 0 -> 6135 bytes
 .../@MLTboxMulticlass/index.html              |  32 +
 .../@MaxChooser/MaxChooser.html               | 104 ++++
 .../+classification/@MaxChooser/MaxChooser.m  |  54 ++
 .../+classification/@MaxChooser/graph.dot     |   6 +
 .../+classification/@MaxChooser/graph.html    |  28 +
 .../+classification/@MaxChooser/graph.map     |   1 +
 .../+classification/@MaxChooser/graph.png     | Bin 0 -> 5337 bytes
 .../+classification/@MaxChooser/index.html    |  32 +
 .../+classification/@SBLR/SBLR.html           | 138 ++++
 doc/+eegtoolkit/+classification/@SBLR/SBLR.m  |  88 +++
 .../+classification/@SBLR/graph.dot           |   6 +
 .../+classification/@SBLR/graph.html          |  28 +
 .../+classification/@SBLR/graph.map           |   1 +
 .../+classification/@SBLR/graph.png           | Bin 0 -> 3710 bytes
 .../+classification/@SBLR/index.html          |  32 +
 .../+classification/@SMFA/SMFA.html           | 193 ++++++
 doc/+eegtoolkit/+classification/@SMFA/SMFA.m  | 143 +++++
 .../+classification/@SMFA/graph.dot           |   6 +
 .../+classification/@SMFA/graph.html          |  28 +
 .../+classification/@SMFA/graph.map           |   1 +
 .../+classification/@SMFA/graph.png           | Bin 0 -> 3906 bytes
 .../+classification/@SMFA/index.html          |  32 +
 .../@Experimenter/Experimenter.html           | 455 ++++++++++++++
 .../+experiment/@Experimenter/Experimenter.m  | 381 +++++++++++
 .../+experiment/@Experimenter/graph.dot       |   6 +
 .../+experiment/@Experimenter/graph.html      |  28 +
 .../+experiment/@Experimenter/graph.map       |   1 +
 .../+experiment/@Experimenter/graph.png       | Bin 0 -> 4968 bytes
 .../+experiment/@Experimenter/index.html      |  32 +
 .../@ResultEvaluator/ResultEvaluator.html     | 136 ++++
 .../@ResultEvaluator/ResultEvaluator.m        |  85 +++
 .../+experiment/@ResultEvaluator/graph.dot    |   6 +
 .../+experiment/@ResultEvaluator/graph.html   |  28 +
 .../+experiment/@ResultEvaluator/graph.map    |   1 +
 .../+experiment/@ResultEvaluator/graph.png    | Bin 0 -> 5619 bytes
 .../+experiment/@ResultEvaluator/index.html   |  32 +
 doc/+eegtoolkit/+featextraction/@CCA/CCA.html | 195 ++++++
 doc/+eegtoolkit/+featextraction/@CCA/CCA.m    | 145 +++++
 .../+featextraction/@CCA/graph.dot            |   6 +
 .../+featextraction/@CCA/graph.html           |  28 +
 .../+featextraction/@CCA/graph.map            |   1 +
 .../+featextraction/@CCA/graph.png            | Bin 0 -> 3321 bytes
 .../+featextraction/@CCA/index.html           |  32 +
 doc/+eegtoolkit/+featextraction/@DWT/DWT.html | 171 +++++
 doc/+eegtoolkit/+featextraction/@DWT/DWT.m    | 121 ++++
 .../+featextraction/@DWT/graph.dot            |   6 +
 .../+featextraction/@DWT/graph.html           |  28 +
 .../+featextraction/@DWT/graph.map            |   1 +
 .../+featextraction/@DWT/graph.png            | Bin 0 -> 3596 bytes
 .../+featextraction/@DWT/index.html           |  32 +
 .../@ERRPFeatures/ERRPFeatures.html           |  86 +++
 .../@ERRPFeatures/ERRPFeatures.m              |  36 ++
 .../+featextraction/@ERRPFeatures/graph.dot   |   6 +
 .../+featextraction/@ERRPFeatures/graph.html  |  28 +
 .../+featextraction/@ERRPFeatures/graph.map   |   1 +
 .../+featextraction/@ERRPFeatures/graph.png   | Bin 0 -> 5437 bytes
 .../+featextraction/@ERRPFeatures/index.html  |  32 +
 doc/+eegtoolkit/+featextraction/@FFT/FFT.html | 139 +++++
 doc/+eegtoolkit/+featextraction/@FFT/FFT.m    |  89 +++
 .../+featextraction/@FFT/graph.dot            |   6 +
 .../+featextraction/@FFT/graph.html           |  28 +
 .../+featextraction/@FFT/graph.map            |   1 +
 .../+featextraction/@FFT/graph.png            | Bin 0 -> 3054 bytes
 .../+featextraction/@FFT/index.html           |  32 +
 .../FeatureExtractionBase.html                | 134 ++++
 .../FeatureExtractionBase.m                   |  69 ++
 .../@FeatureExtractionBase/graph.dot          |   6 +
 .../@FeatureExtractionBase/graph.html         |  28 +
 .../@FeatureExtractionBase/graph.map          |   1 +
 .../@FeatureExtractionBase/graph.png          | Bin 0 -> 6637 bytes
 .../@FeatureExtractionBase/index.html         |  32 +
 .../+featextraction/@Goertzel/Goertzel.html   | 150 +++++
 .../+featextraction/@Goertzel/Goertzel.m      | 100 +++
 .../+featextraction/@Goertzel/graph.dot       |   6 +
 .../+featextraction/@Goertzel/graph.html      |  28 +
 .../+featextraction/@Goertzel/graph.map       |   1 +
 .../+featextraction/@Goertzel/graph.png       | Bin 0 -> 4176 bytes
 .../+featextraction/@Goertzel/index.html      |  32 +
 .../+featextraction/@L1MCCA/L1MCCA.html       |  77 +++
 .../+featextraction/@L1MCCA/L1MCCA.m          |  27 +
 .../+featextraction/@L1MCCA/graph.dot         |   6 +
 .../+featextraction/@L1MCCA/graph.html        |  28 +
 .../+featextraction/@L1MCCA/graph.map         |   1 +
 .../+featextraction/@L1MCCA/graph.png         | Bin 0 -> 4313 bytes
 .../+featextraction/@L1MCCA/index.html        |  32 +
 .../@MLR_Transf/MLR_Transf.html               | 114 ++++
 .../+featextraction/@MLR_Transf/MLR_Transf.m  |  64 ++
 .../+featextraction/@MLR_Transf/graph.dot     |   6 +
 .../+featextraction/@MLR_Transf/graph.html    |  28 +
 .../+featextraction/@MLR_Transf/graph.map     |   1 +
 .../+featextraction/@MLR_Transf/graph.png     | Bin 0 -> 5170 bytes
 .../+featextraction/@MLR_Transf/index.html    |  32 +
 .../@PSDExtractionBase/PSDExtractionBase.html |  55 ++
 .../@PSDExtractionBase/PSDExtractionBase.m    |   7 +
 .../@PSDExtractionBase/graph.dot              |   6 +
 .../@PSDExtractionBase/graph.html             |  28 +
 .../@PSDExtractionBase/graph.map              |   1 +
 .../@PSDExtractionBase/graph.png              | Bin 0 -> 6642 bytes
 .../@PSDExtractionBase/index.html             |  32 +
 .../+featextraction/@PWelch/PWelch.html       | 167 +++++
 .../+featextraction/@PWelch/PWelch.m          | 117 ++++
 .../+featextraction/@PWelch/graph.dot         |   6 +
 .../+featextraction/@PWelch/graph.html        |  28 +
 .../+featextraction/@PWelch/graph.map         |   1 +
 .../+featextraction/@PWelch/graph.png         | Bin 0 -> 4181 bytes
 .../+featextraction/@PWelch/index.html        |  32 +
 .../PWelchExperimental.html                   | 183 ++++++
 .../@PWelchExperimental/PWelchExperimental.m  | 133 ++++
 .../@PWelchExperimental/graph.dot             |   6 +
 .../@PWelchExperimental/graph.html            |  28 +
 .../@PWelchExperimental/graph.map             |   1 +
 .../@PWelchExperimental/graph.png             | Bin 0 -> 6940 bytes
 .../@PWelchExperimental/index.html            |  32 +
 .../+featextraction/@PYAR/PYAR.html           | 147 +++++
 doc/+eegtoolkit/+featextraction/@PYAR/PYAR.m  |  97 +++
 .../+featextraction/@PYAR/graph.dot           |   6 +
 .../+featextraction/@PYAR/graph.html          |  28 +
 .../+featextraction/@PYAR/graph.map           |   1 +
 .../+featextraction/@PYAR/graph.png           | Bin 0 -> 3778 bytes
 .../+featextraction/@PYAR/index.html          |  32 +
 .../+featextraction/@RawSignal/RawSignal.html |  77 +++
 .../+featextraction/@RawSignal/RawSignal.m    |  27 +
 .../+featextraction/@RawSignal/graph.dot      |   6 +
 .../+featextraction/@RawSignal/graph.html     |  28 +
 .../+featextraction/@RawSignal/graph.map      |   1 +
 .../+featextraction/@RawSignal/graph.png      | Bin 0 -> 4861 bytes
 .../+featextraction/@RawSignal/index.html     |  32 +
 .../+featextraction/@STFT/STFT.html           | 151 +++++
 doc/+eegtoolkit/+featextraction/@STFT/STFT.m  | 101 +++
 .../+featextraction/@STFT/graph.dot           |   6 +
 .../+featextraction/@STFT/graph.html          |  28 +
 .../+featextraction/@STFT/graph.map           |   1 +
 .../+featextraction/@STFT/graph.png           | Bin 0 -> 3374 bytes
 .../+featextraction/@STFT/index.html          |  32 +
 .../+featselection/@FEAST/FEAST.html          | 126 ++++
 doc/+eegtoolkit/+featselection/@FEAST/FEAST.m |  76 +++
 .../+featselection/@FEAST/graph.dot           |   6 +
 .../+featselection/@FEAST/graph.html          |  28 +
 .../+featselection/@FEAST/graph.map           |   1 +
 .../+featselection/@FEAST/graph.png           | Bin 0 -> 3946 bytes
 .../+featselection/@FEAST/index.html          |  32 +
 .../FeatureSelectionBase.html                 |  93 +++
 .../FeatureSelectionBase.m                    |  31 +
 .../@FeatureSelectionBase/graph.dot           |   6 +
 .../@FeatureSelectionBase/graph.html          |  28 +
 .../@FeatureSelectionBase/graph.map           |   1 +
 .../@FeatureSelectionBase/graph.png           | Bin 0 -> 6599 bytes
 .../@FeatureSelectionBase/index.html          |  32 +
 doc/+eegtoolkit/+featselection/@PCA/PCA.html  |  82 +++
 doc/+eegtoolkit/+featselection/@PCA/PCA.m     |  32 +
 doc/+eegtoolkit/+featselection/@PCA/graph.dot |   6 +
 .../+featselection/@PCA/graph.html            |  28 +
 doc/+eegtoolkit/+featselection/@PCA/graph.map |   1 +
 doc/+eegtoolkit/+featselection/@PCA/graph.png | Bin 0 -> 3438 bytes
 .../+featselection/@PCA/index.html            |  32 +
 doc/+eegtoolkit/+featselection/@SVD/SVD.html  |  82 +++
 doc/+eegtoolkit/+featselection/@SVD/SVD.m     |  32 +
 doc/+eegtoolkit/+featselection/@SVD/graph.dot |   6 +
 .../+featselection/@SVD/graph.html            |  28 +
 doc/+eegtoolkit/+featselection/@SVD/graph.map |   1 +
 doc/+eegtoolkit/+featselection/@SVD/graph.png | Bin 0 -> 3482 bytes
 .../+featselection/@SVD/index.html            |  32 +
 .../+preprocessing/@Amuse/Amuse.html          | 152 +++++
 doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.m | 102 +++
 .../+preprocessing/@Amuse/graph.dot           |   6 +
 .../+preprocessing/@Amuse/graph.html          |  28 +
 .../+preprocessing/@Amuse/graph.map           |   1 +
 .../+preprocessing/@Amuse/graph.png           | Bin 0 -> 3920 bytes
 .../+preprocessing/@Amuse/index.html          |  32 +
 .../@DigitalFilter/DigitalFilter.html         | 100 +++
 .../@DigitalFilter/DigitalFilter.m            |  50 ++
 .../+preprocessing/@DigitalFilter/graph.dot   |   6 +
 .../+preprocessing/@DigitalFilter/graph.html  |  28 +
 .../+preprocessing/@DigitalFilter/graph.map   |   1 +
 .../+preprocessing/@DigitalFilter/graph.png   | Bin 0 -> 4874 bytes
 .../+preprocessing/@DigitalFilter/index.html  |  32 +
 .../+preprocessing/@FastICA/FastICA.html      |  97 +++
 .../+preprocessing/@FastICA/FastICA.m         |  47 ++
 .../+preprocessing/@FastICA/graph.dot         |   6 +
 .../+preprocessing/@FastICA/graph.html        |  28 +
 .../+preprocessing/@FastICA/graph.map         |   1 +
 .../+preprocessing/@FastICA/graph.png         | Bin 0 -> 4316 bytes
 .../+preprocessing/@FastICA/index.html        |  32 +
 .../@PreprocessingBase/PreprocessingBase.html |  95 +++
 .../@PreprocessingBase/PreprocessingBase.m    |  32 +
 .../@PreprocessingBase/graph.dot              |   6 +
 .../@PreprocessingBase/graph.html             |  28 +
 .../@PreprocessingBase/graph.map              |   1 +
 .../@PreprocessingBase/graph.png              | Bin 0 -> 6235 bytes
 .../@PreprocessingBase/index.html             |  32 +
 .../@Rereferencing/Rereferencing.html         |  95 +++
 .../@Rereferencing/Rereferencing.m            |  45 ++
 .../+preprocessing/@Rereferencing/graph.dot   |   6 +
 .../+preprocessing/@Rereferencing/graph.html  |  28 +
 .../+preprocessing/@Rereferencing/graph.map   |   1 +
 .../+preprocessing/@Rereferencing/graph.png   | Bin 0 -> 5129 bytes
 .../+preprocessing/@Rereferencing/index.html  |  32 +
 .../@SampleSelection/SampleSelection.html     | 143 +++++
 .../@SampleSelection/SampleSelection.m        |  93 +++
 .../+preprocessing/@SampleSelection/graph.dot |   6 +
 .../@SampleSelection/graph.html               |  28 +
 .../+preprocessing/@SampleSelection/graph.map |   1 +
 .../+preprocessing/@SampleSelection/graph.png | Bin 0 -> 5780 bytes
 .../@SampleSelection/index.html               |  32 +
 .../@Windsorize/Windsorize.html               | 114 ++++
 .../+preprocessing/@Windsorize/Windsorize.m   |  64 ++
 .../+preprocessing/@Windsorize/graph.dot      |   6 +
 .../+preprocessing/@Windsorize/graph.html     |  28 +
 .../+preprocessing/@Windsorize/graph.map      |   1 +
 .../+preprocessing/@Windsorize/graph.png      | Bin 0 -> 5066 bytes
 .../+preprocessing/@Windsorize/index.html     |  32 +
 .../@FusionInstanceSet/FusionInstanceSet.html |  83 +++
 .../@FusionInstanceSet/FusionInstanceSet.m    |  33 +
 .../+util/@FusionInstanceSet/graph.dot        |   6 +
 .../+util/@FusionInstanceSet/graph.html       |  28 +
 .../+util/@FusionInstanceSet/graph.map        |   1 +
 .../+util/@FusionInstanceSet/graph.png        | Bin 0 -> 5944 bytes
 .../+util/@FusionInstanceSet/index.html       |  32 +
 .../+util/@InstanceSet/InstanceSet.html       | 327 ++++++++++
 .../+util/@InstanceSet/InstanceSet.m          | 238 +++++++
 doc/+eegtoolkit/+util/@InstanceSet/graph.dot  |   6 +
 doc/+eegtoolkit/+util/@InstanceSet/graph.html |  28 +
 doc/+eegtoolkit/+util/@InstanceSet/graph.map  |   1 +
 doc/+eegtoolkit/+util/@InstanceSet/graph.png  | Bin 0 -> 4769 bytes
 doc/+eegtoolkit/+util/@InstanceSet/index.html |  32 +
 .../@L1MCCAInstanceSet/L1MCCAInstanceSet.html | 125 ++++
 .../@L1MCCAInstanceSet/L1MCCAInstanceSet.m    |  74 +++
 .../+util/@L1MCCAInstanceSet/graph.dot        |   6 +
 .../+util/@L1MCCAInstanceSet/graph.html       |  28 +
 .../+util/@L1MCCAInstanceSet/graph.map        |   1 +
 .../+util/@L1MCCAInstanceSet/graph.png        | Bin 0 -> 6710 bytes
 .../+util/@L1MCCAInstanceSet/index.html       |  32 +
 .../+util/@LSLWrapper/LSLWrapper.html         | 310 +++++++++
 .../+util/@LSLWrapper/LSLWrapper.m            | 260 ++++++++
 doc/+eegtoolkit/+util/@LSLWrapper/graph.dot   |   6 +
 doc/+eegtoolkit/+util/@LSLWrapper/graph.html  |  28 +
 doc/+eegtoolkit/+util/@LSLWrapper/graph.map   |   1 +
 doc/+eegtoolkit/+util/@LSLWrapper/graph.png   | Bin 0 -> 5124 bytes
 doc/+eegtoolkit/+util/@LSLWrapper/index.html  |  32 +
 .../+util/@RawSignalSet/RawSignalSet.html     | 112 ++++
 .../+util/@RawSignalSet/RawSignalSet.m        |  62 ++
 doc/+eegtoolkit/+util/@RawSignalSet/graph.dot |   6 +
 .../+util/@RawSignalSet/graph.html            |  28 +
 doc/+eegtoolkit/+util/@RawSignalSet/graph.map |   1 +
 doc/+eegtoolkit/+util/@RawSignalSet/graph.png | Bin 0 -> 5436 bytes
 .../+util/@RawSignalSet/index.html            |  32 +
 .../+util/@ResultSet/ResultSet.html           | 111 ++++
 doc/+eegtoolkit/+util/@ResultSet/ResultSet.m  |  60 ++
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diff --git a/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m b/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m
index 8edc02e..031a77f 100644
--- a/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m
+++ b/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m
@@ -1,3 +1,23 @@
+% Abstract class for aggregation. Implement the functions for any
+% fusion methodology (e.g. late fusion, VLAD, channel concatenation, etc.)
+% 
+% Properties:
+% featextractors: cell array with the the feature extractors to be used on
+% the trials. Each cell contains a featextraction object, and the trials
+% are given to each of the objects within the Experimenter class
+% instanceSet: output - the aggregated features. Can be a simple
+% InstanceSet or the extended FusionInstanceSet
+% 
+% Functions:
+%Implement this function to process the trials of each featextraction
+%object in the cell array featextractors. It should store in the
+%instanceSet property the features.
+%   obj.aggregate();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
 classdef (Abstract) AggregatorBase < handle
     
     properties
diff --git a/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m b/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
index db4f636..ad07e26 100644
--- a/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
+++ b/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
@@ -1,3 +1,30 @@
+% Abstract class for classification. Implement the functions for any
+% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+% 
+% Properties:
+% instanceSet: the training/test set in an InstanceSet structure
+% 
+% Functions:
+%Implement this function to train the classification models. Each
+%implementation should define the type of models that are to be trained by
+%the build function.
+%   obj = obj.build();
+%Implement this function to apply the classification models to the provided
+%instance, where instance is a matrix #instances x #features including the
+%instances. The function should return the following three outputs; 1)
+%output, the classified labels of the instances (#instances x 1), 2)
+%probabilities, the probabilities for the output label (instances x 1) and
+%3) ranking, a matrix #instances x #classes with the probabilities of each
+%instance for each class (used for multiclass classification).
+%   [output, probabilities, ranking] = obj.classifyInstance(instance);
+%Implement this function to reset the classifier (e.g. delete the stored
+%classification models
+%   obj.reset();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
 classdef (Abstract) ClassifierBase < handle
     
     properties
@@ -5,7 +32,7 @@
     end
     
     methods (Abstract = true)
-        obj = classifyInstance(obj);
+        [output, probabilities, ranking] = classifyInstance(obj,instance);
         obj = build(obj);
         obj = reset(obj);
         configInfo = getConfigInfo(obj);
diff --git a/+eegtoolkit/+experiment/@Experimenter/Experimenter.m b/+eegtoolkit/+experiment/@Experimenter/Experimenter.m
index ffb7846..9b28677 100644
--- a/+eegtoolkit/+experiment/@Experimenter/Experimenter.m
+++ b/+eegtoolkit/+experiment/@Experimenter/Experimenter.m
@@ -3,20 +3,22 @@
 %Before running an experiment all the required properties must be set.
 % Required:
 % - session
-% - transformer
+% - featextraction
 % - evalMethod
-% - classifier
+% - classification
 % Optional:
-% - extractor
+% - featselection
+% - aggregator
+% - preprocessing
 %
 % to run the experiment execute the "run()" method.
 % Example:
 % experiment = eegtoolkit.experiment.Experimenter;
 % experiment.session = eegtoolkit.util.Session;
 % experiment.session.loadSubject(1);
-% experiment.transformer = eegtoolkit.transformer.PWelchTransformer;
-% experiment.extractor = eegtoolkit.extractor.FEASTFilter;
-% experiment.classifier = eegtoolkit.classifier.LIBSVMClassifier;
+% experiment.transformer = eegtoolkit.featextraction.PWelch;
+% experiment.extractor = eegtoolkit.featselection.FEAST;
+% experiment.classification = eegtoolkit.classification.LIBSVM;
 % experiment.evalMethod = experiment.evalMethod.EVAL_METHOD_LOSO;
 % experiment.run;
 % results = experiment.results;
diff --git a/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m b/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
index 7e93bbf..29ef454 100644
--- a/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
+++ b/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
@@ -1,3 +1,21 @@
+% Abstract class for feature extraction. Implement the functions for any
+% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+% rereferencing, etc.
+% 
+% Properties:
+% instanceSet: Output - the features in an InstanceSet structure
+% trials: Input - the signals in a cell of Trial structures
+% 
+% Functions:
+%Implement this function to extract the features from the input Trials 
+%and return the features in an instanceSet
+%   out = obj.extract(in);
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+
 classdef (Abstract) FeatureExtractionBase < handle
     %Base class for a feature transformer
     %For writing your own FeatureTransformer extend this class and
diff --git a/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m b/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m
index 3a77365..7101cc1 100644
--- a/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m
+++ b/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m
@@ -1,6 +1,21 @@
+% Abstract class for feature selection. Implement the functions for any
+% feature selection method (e.g. PCA, SVD, FEAST, etc.)
+% 
+% Properties:
+% originalInstanceSet: Input - the original instanceSet with the features
+% filteredInstanceSet: Output - the filtered instanceSet
+% 
+% Functions:
+%Implement this function to process the originalInstanceSet trials and 
+%return the filteredInstanceSet
+%   obj.compute();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
 classdef (Abstract) FeatureSelectionBase < handle
-    %Base class for a FeatureExtractor
-    %Subclasses must implement the filter method
+    
     properties
         originalInstanceSet; % Input: The original dataset
         filteredInstanceSet; % Output: The filtered dataset
diff --git a/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m b/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m
index e426bd3..9abae63 100644
--- a/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m
+++ b/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m
@@ -1,3 +1,20 @@
+% Abstract class for preprocessing. Implement the functions for any
+% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+% rereferencing, etc.
+% 
+% Properties:
+% originalTrials: cell array with the trials to be processed
+% processedTrials: the processed trials to be returned
+% 
+% Functions:
+%Implement this function to process the in trials and return the processed
+%trials (out)
+%   out = obj.process(in);
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
 classdef PreprocessingBase < handle
     
     properties
diff --git a/+eegtoolkit/+util/@InstanceSet/InstanceSet.m b/+eegtoolkit/+util/@InstanceSet/InstanceSet.m
index 5e88dbd..fbe2fc4 100644
--- a/+eegtoolkit/+util/@InstanceSet/InstanceSet.m
+++ b/+eegtoolkit/+util/@InstanceSet/InstanceSet.m
@@ -1,6 +1,45 @@
+% A class for describing a set of instances and labels
+% 
+% Properties:
+% -instances : a m x n matrix where m = # instances and n =
+% # features
+% -labels: a m x 1 matrix containing the labels for each
+% instance
+% -K: a m x m matrix containing the kernel of the instances
+% required only for the Fast vesrion of LibSVM
+%
+% Functions:
+%Construct an instanceSet
+%   IS = eegtoolkit.util.InstanceSet(instances, labels)
+%Compute the kernel
+%   K = IS.computeKernel(kernel, gamma, maxlag, scaleopt)
+% kernel can be one of 'linear' (default),'rbf','chi','xcorr','spearman',
+% 'correlation','cosine','euclidean','seuclidean','mahalanobis'
+%Get the training kernel with indexes in the trainidx vector
+%   Ktrain = IS.getTrainKernel(trainidx)
+%Get the test kernel with test indexes testidx and train indexes trainidx
+%   Ktest = IS.getTestKernel(trainidx, testidx)
+%Get instances of specific indices in vector idx
+%   instance = IS.getInstancesWithIndices(idx)
+%Get the instances of a specific label
+%   instances = IS.getInstancesForLabel(label)
+%Get the indices corresponding to a specific label
+%   indices = IS.getInstanceIndicesForLabel(label)
+%Get the instances including the labels as the last row
+%   dataset = getDataset(IS)
+%Get the instances with specific indices. The last column of the matrix 
+%will contain the label.
+%   dataset = IS.getDatasetWithIndices(idx)
+%Remove instances with specific indices. A new InstanceSet object is 
+%returned by this function without the specified instances
+%   IS = IS.removeInstancesWithIndices(idx)
+% Write the dataset to a csv file
+%   IS.writeCSV(csvname)
+%Write the dataset to a weka-readable file (arff). The whole dataset is
+%written if the indices are not given (function called with 1 argument)
+%   IS.writeArff(fname, indices)
+
 classdef InstanceSet
-    % A class for describing a set of instances and labels
-    
     properties (Access = public)
         instances; % the instances
         labels; % the labels
@@ -10,10 +49,7 @@
     methods
         function IS = InstanceSet(instances, labels)
             % obj = InstanceSet(instances, labels)
-            % -instances : a m x n matrix where m = instances and n =
-            % features
-            % -labels: a m x 1 matrix containing the labels for each
-            % instance
+            
             if nargin == 1
                 [~, cols] = size(instances);
                 IS.instances = instances(:,1:cols-1);
@@ -48,13 +84,13 @@
                     n = size(IS.instances,1);
                     mOnes = ones(1,m); D = zeros(m,n);
                     for i=1:n
-                      yi = IS.instances(i,:);  yiRep = yi( mOnes, : );
-                      s = yiRep + IS.instances;    d = yiRep - IS.instances;
-                      D(:,i) = sum( d.^2 ./ (s+eps), 2 );
+                        yi = IS.instances(i,:);  yiRep = yi( mOnes, : );
+                        s = yiRep + IS.instances;    d = yiRep - IS.instances;
+                        D(:,i) = sum( d.^2 ./ (s+eps), 2 );
                     end
                     D = D/2;
                     K = exp(-gamma.*D);
-%                     error('chi kernel not implemented yet');
+                    %                     error('chi kernel not implemented yet');
                 case 'xcorr'
                     K = zeros(size(IS.instances,1));
                     if size(IS.instances,2) < 500 % if memory allows it go for the vectorized version
@@ -169,7 +205,7 @@ function writeArff(IS, fname, indices)
                 is1.writeArff(sprintf('test%s', fname));
                 is2.writeArff(sprintf('train%s',fname));
                 return;
-            else 
+            else
                 data = IS.getDataset();
             end
             %             data = horzcat(IS.instances,floor(IS.labels));
diff --git a/+eegtoolkit/+util/@Session/Session.m b/+eegtoolkit/+util/@Session/Session.m
index bc532fa..eb89757 100644
--- a/+eegtoolkit/+util/@Session/Session.m
+++ b/+eegtoolkit/+util/@Session/Session.m
@@ -1,10 +1,17 @@
 % SESSION class
 % Session I/O, splitting sessions into trials and applying filters
 %
-% Usage:
+% Properties:
+% trials: A cell array with the Trials of the loaded sessions.
+% filt: Filter to be applied when data is loaded
+% sessions: Cell array with the filenames of the dataset
+% subjectids: Vector with the subject ids corresponding to the loaded trials
+% sessionids: Vector with the session ids corresponding to the loaded trials
+%
+% Functions:
 %init a session
 %   session = eegtoolkit.util.Session();
-%init a session with a filter (created with 'filterbuilder' function)
+%init a session with a filter (created with 'filterbuilder')
 %   session = eegtoolkit.util.Session(filt);
 %load trials for a subject
 %   session.loadSubject(subjectid);
@@ -18,6 +25,14 @@
 %   session.applyFilter(filt);
 %
 %
+%DATASETS
+%1. SSVEP Dataset I (SINGLE)
+%2. SSVEP Dataset II (MULTI)
+%3. SSVEP Dataset III (EPOC-MULTI)
+%4. SSVEP Dataset SCCN
+%5. ERRP Dataset
+%6. MI Dataset
+
 classdef Session < handle
     
     properties (Constant)
@@ -31,13 +46,7 @@
         sessionids;
     end
     
-    %DATASETS
-    %1. SSVEP Dataset I (SINGLE)
-    %2. SSVEP Dataset II (MULTI)
-    %3. SSVEP Dataset III (EPOC-MULTI)
-    %4. SSVEP Dataset SCCN
-    %5. ERRP Dataset 
-    %6. MI Dataset
+    
     methods (Access = public)
         function S = Session()
             %S = eegtoolkit.util.Session();
@@ -209,7 +218,7 @@
             S.sessions{3,11,3} = 'U011c';
             S.sessions{3,11,4} = 'U011d';
             S.sessions{3,11,5} = 'U011e';
-       
+            
             %SCCN dataset
             S.sessions{4,1,1} = 's1';
             S.sessions{4,2,1} = 's2';
@@ -254,7 +263,7 @@
             S.sessions{7,9,2} = 'B09T.mat';
             
             %MI dataset
-%             S.sessions{6,1,1} = ;
+            %             S.sessions{6,1,1} = ;
             
             
             S.subjectids = [];
@@ -360,7 +369,7 @@
                     end
                 case 5
                     %ERRP Dataset
-                    SAMPLING_RATE = 256;                    
+                    SAMPLING_RATE = 256;
                     %range of trial in milliseconds based on the stimulus
                     %event
                     range = [200,800];
diff --git a/+eegtoolkit/+util/@Trial/Trial.m b/+eegtoolkit/+util/@Trial/Trial.m
index de32cd1..f3a4b06 100644
--- a/+eegtoolkit/+util/@Trial/Trial.m
+++ b/+eegtoolkit/+util/@Trial/Trial.m
@@ -1,5 +1,20 @@
+% A class that defines a Trial
+% 
+% Properties:
+% signal: the signal of the trial, matrix m x n, where m is the channels
+% and n the samples
+% label: a label for the trial (typically assigned with the frequency that is calculated using DIN data)
+% duration: the duration of the trial in seconds
+% samplingRate: the samling rate used to capture the signal
+% subjectid: the subject from whom the trial was recorded
+% sessionid: the session id
+% type: the type of the trial. Supported types of trials:
+% SSVEP = 1;
+% ERRP = 2;
+% MI = 3;
+
 classdef Trial < handle
-    %A class that defines a Trial
+    
     
     properties (Constant)
         %Type of trial
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html
new file mode 100644
index 0000000..c987680
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html
@@ -0,0 +1,101 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of AggregatorBase</title>
+  <meta name="keywords" content="AggregatorBase">
+  <meta name="description" content="Abstract class for aggregation. Implement the functions for any">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@AggregatorBase</a> &gt; AggregatorBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>AggregatorBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>Abstract class for aggregation. Implement the functions for any</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Abstract class for aggregation. Implement the functions for any
+ fusion methodology (e.g. late fusion, VLAD, channel concatenation, etc.)
+ 
+ Properties:
+ featextractors: cell array with the the feature extractors to be used on
+ the trials. Each cell contains a featextraction object, and the trials
+ are given to each of the objects within the Experimenter class
+ instanceSet: output - the aggregated features. Can be a simple
+ InstanceSet or the extended FusionInstanceSet
+ 
+ Functions:
+Implement this function to process the trials of each featextraction
+object in the cell array featextractors. It should store in the
+instanceSet property the features.
+   obj.aggregate();
+Info &amp; run time so that the experiments are easily documented. configInfo
+is a string with the configuration information and time is of type double.
+   configInfo = obj.getConfigInfo();
+   time = obj.getTime();</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="AggregatorBase.html" class="code" title="">AggregatorBase</a>	Abstract class for aggregation. Implement the functions for any</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="AggregatorBase.html" class="code" title="">AggregatorBase</a>	Abstract class for aggregation. Implement the functions for any</li></ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="AggregatorBase.m">AggregatorBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Abstract class for aggregation. Implement the functions for any</span>
+0002 <span class="comment">% fusion methodology (e.g. late fusion, VLAD, channel concatenation, etc.)</span>
+0003 <span class="comment">%</span>
+0004 <span class="comment">% Properties:</span>
+0005 <span class="comment">% featextractors: cell array with the the feature extractors to be used on</span>
+0006 <span class="comment">% the trials. Each cell contains a featextraction object, and the trials</span>
+0007 <span class="comment">% are given to each of the objects within the Experimenter class</span>
+0008 <span class="comment">% instanceSet: output - the aggregated features. Can be a simple</span>
+0009 <span class="comment">% InstanceSet or the extended FusionInstanceSet</span>
+0010 <span class="comment">%</span>
+0011 <span class="comment">% Functions:</span>
+0012 <span class="comment">%Implement this function to process the trials of each featextraction</span>
+0013 <span class="comment">%object in the cell array featextractors. It should store in the</span>
+0014 <span class="comment">%instanceSet property the features.</span>
+0015 <span class="comment">%   obj.aggregate();</span>
+0016 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0017 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0018 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0019 <span class="comment">%   time = obj.getTime();</span>
+0020 
+0021 classdef (Abstract) <a href="AggregatorBase.html" class="code" title="">AggregatorBase</a> &lt; handle
+0022     
+0023     properties
+0024         featextractors;
+0025         instanceSet;
+0026     <span class="keyword">end</span>
+0027     
+0028     methods (Abstract = true)
+0029         obj = aggregate(obj);
+0030         configInfo = getConfigInfo(obj);
+0031         time = getTime(obj);
+0032     <span class="keyword">end</span>
+0033     
+0034 <span class="keyword">end</span>
+0035</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m
new file mode 100644
index 0000000..031a77f
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.m
@@ -0,0 +1,35 @@
+% Abstract class for aggregation. Implement the functions for any
+% fusion methodology (e.g. late fusion, VLAD, channel concatenation, etc.)
+% 
+% Properties:
+% featextractors: cell array with the the feature extractors to be used on
+% the trials. Each cell contains a featextraction object, and the trials
+% are given to each of the objects within the Experimenter class
+% instanceSet: output - the aggregated features. Can be a simple
+% InstanceSet or the extended FusionInstanceSet
+% 
+% Functions:
+%Implement this function to process the trials of each featextraction
+%object in the cell array featextractors. It should store in the
+%instanceSet property the features.
+%   obj.aggregate();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+classdef (Abstract) AggregatorBase < handle
+    
+    properties
+        featextractors;
+        instanceSet;
+    end
+    
+    methods (Abstract = true)
+        obj = aggregate(obj);
+        configInfo = getConfigInfo(obj);
+        time = getTime(obj);
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.dot b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.dot
new file mode 100644
index 0000000..ed68ee0
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  AggregatorBase -> AggregatorBase;
+
+  AggregatorBase [URL="AggregatorBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html
new file mode 100644
index 0000000..63f8728
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@AggregatorBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@AggregatorBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="AggregatorBase.html" title="AggregatorBase" alt="" coords="185,29,180,22,168,15,148,10,123,7,95,5,67,7,42,10,22,15,9,22,5,29,9,37,22,43,42,49,67,52,95,53,123,52,148,49,168,43,180,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.map b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.map
new file mode 100644
index 0000000..7ed2ecc
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="AggregatorBase.html" title="AggregatorBase" alt="" coords="185,29,180,22,168,15,148,10,123,7,95,5,67,7,42,10,22,15,9,22,5,29,9,37,22,43,42,49,67,52,95,53,123,52,148,49,168,43,180,37">
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diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/index.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/index.html
new file mode 100644
index 0000000..c8f11ba
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@AggregatorBase</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@AggregatorBase">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@AggregatorBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@AggregatorBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="AggregatorBase.html">AggregatorBase</a></td><td>Abstract class for aggregation. Implement the functions for any </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html
new file mode 100644
index 0000000..7725575
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html
@@ -0,0 +1,83 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ChannelAveraging</title>
+  <meta name="keywords" content="ChannelAveraging">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelAveraging</a> &gt; ChannelAveraging.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ChannelAveraging
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelAveraging.html" class="code" title="">ChannelAveraging</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelAveraging.html" class="code" title="">ChannelAveraging</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CA = ChannelAveraging(CA)</a></li><li><a href="#_sub2" class="code">function CA = aggregate(CA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CA)</a></li><li><a href="#_sub4" class="code">function time = getTime(CA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ChannelAveraging.m">ChannelAveraging.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="ChannelAveraging.html" class="code" title="">ChannelAveraging</a> &lt; eegtoolkit.aggregation.AggregatorBase;
+0002     
+0003     properties
+0004     <span class="keyword">end</span>
+0005     
+0006     methods
+0007         
+0008         <a name="_sub0" href="#_subfunctions" class="code">function CA = ChannelAveraging(CA)</a>
+0009         <span class="keyword">end</span>
+0010         
+0011         <a name="_sub1" href="#_subfunctions" class="code">function CA = aggregate(CA)</a>
+0012             numExtr = length(CA.featextractors);
+0013             numInstances = CA.featextractors{1}.getInstanceSet.getNumInstances;
+0014             numFeatures = CA.featextractors{1}.getInstanceSet.getNumFeatures;
+0015             fused = zeros(numInstances,numFeatures,numExtr);
+0016             <span class="keyword">for</span> i=1:numExtr
+0017                 fused(:,:,i) = CA.featextractors{i}.getInstances;
+0018             <span class="keyword">end</span>
+0019             fusedMean = mean(fused,3);
+0020             CA.instanceSet = eegtoolkit.util.InstanceSet(fusedMean,CA.featextractors{1}.getLabels);
+0021         <span class="keyword">end</span>
+0022         
+0023         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CA)</a>
+0024             configInfo = <span class="string">'ChannelAveraging'</span>;
+0025         <span class="keyword">end</span>
+0026         
+0027         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(CA)</a>
+0028             time = 0;
+0029         <span class="keyword">end</span>
+0030     <span class="keyword">end</span>
+0031     
+0032 <span class="keyword">end</span>
+0033</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.m b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.m
new file mode 100644
index 0000000..70025af
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.m
@@ -0,0 +1,33 @@
+classdef ChannelAveraging < eegtoolkit.aggregation.AggregatorBase;
+    
+    properties
+    end
+    
+    methods
+        
+        function CA = ChannelAveraging(CA)
+        end
+        
+        function CA = aggregate(CA)
+            numExtr = length(CA.featextractors);
+            numInstances = CA.featextractors{1}.getInstanceSet.getNumInstances;
+            numFeatures = CA.featextractors{1}.getInstanceSet.getNumFeatures;
+            fused = zeros(numInstances,numFeatures,numExtr);
+            for i=1:numExtr
+                fused(:,:,i) = CA.featextractors{i}.getInstances;
+            end
+            fusedMean = mean(fused,3);
+            CA.instanceSet = eegtoolkit.util.InstanceSet(fusedMean,CA.featextractors{1}.getLabels);
+        end
+        
+        function configInfo = getConfigInfo(CA)
+            configInfo = 'ChannelAveraging';
+        end
+        
+        function time = getTime(CA)
+            time = 0;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.dot b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.dot
new file mode 100644
index 0000000..361dae9
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ChannelAveraging -> ChannelAveraging;
+
+  ChannelAveraging [URL="ChannelAveraging.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.html
new file mode 100644
index 0000000..1f109ac
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelAveraging</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelAveraging</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelAveraging" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ChannelAveraging.html" title="ChannelAveraging" alt="" coords="211,29,206,22,191,15,169,10,140,7,108,5,76,7,47,10,25,15,10,22,5,29,10,37,25,43,47,49,76,52,108,53,140,52,169,49,191,43,206,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.map b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/index.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/index.html
new file mode 100644
index 0000000..43b615a
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@ChannelAveraging</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@ChannelAveraging</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ChannelAveraging.html">ChannelAveraging</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html
new file mode 100644
index 0000000..6e777be
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html
@@ -0,0 +1,84 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ChannelConcat</title>
+  <meta name="keywords" content="ChannelConcat">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelConcat</a> &gt; ChannelConcat.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ChannelConcat
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelConcat.html" class="code" title="">ChannelConcat</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelConcat.html" class="code" title="">ChannelConcat</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CC = ChannelConcat(CC)</a></li><li><a href="#_sub2" class="code">function CC = aggregate(CC)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CC)</a></li><li><a href="#_sub4" class="code">function time = getTime(CC)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ChannelConcat.m">ChannelConcat.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="ChannelConcat.html" class="code" title="">ChannelConcat</a> &lt; eegtoolkit.aggregation.AggregatorBase;
+0002     
+0003     properties
+0004     <span class="keyword">end</span>
+0005     
+0006     methods
+0007         
+0008         <a name="_sub0" href="#_subfunctions" class="code">function CC = ChannelConcat(CC)</a>
+0009         <span class="keyword">end</span>
+0010         
+0011         <a name="_sub1" href="#_subfunctions" class="code">function CC = aggregate(CC)</a>
+0012             numExtract = length(CC.featextractors);
+0013             fused = [];
+0014             <span class="keyword">for</span> i=1:numExtract
+0015                 fused = horzcat(fused,CC.featextractors{i}.getInstances);
+0016             <span class="keyword">end</span>
+0017 <span class="comment">%             [~,y] = size(fused);</span>
+0018 <span class="comment">%             ind = randperm(y);</span>
+0019 <span class="comment">%             fused = fused(:,ind);</span>
+0020             CC.instanceSet = eegtoolkit.util.InstanceSet(fused,CC.featextractors{1}.getLabels);
+0021         <span class="keyword">end</span>
+0022         
+0023         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CC)</a>
+0024             configInfo = <span class="string">'ChannelConcat'</span>;
+0025         <span class="keyword">end</span>
+0026         
+0027                 
+0028         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(CC)</a>
+0029             time = 0;
+0030         <span class="keyword">end</span>
+0031     <span class="keyword">end</span>
+0032     
+0033 <span class="keyword">end</span>
+0034</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.m b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.m
new file mode 100644
index 0000000..dacd315
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.m
@@ -0,0 +1,34 @@
+classdef ChannelConcat < eegtoolkit.aggregation.AggregatorBase;
+    
+    properties
+    end
+    
+    methods
+        
+        function CC = ChannelConcat(CC)
+        end
+        
+        function CC = aggregate(CC)
+            numExtract = length(CC.featextractors);
+            fused = [];
+            for i=1:numExtract
+                fused = horzcat(fused,CC.featextractors{i}.getInstances);
+            end
+%             [~,y] = size(fused);
+%             ind = randperm(y);
+%             fused = fused(:,ind);
+            CC.instanceSet = eegtoolkit.util.InstanceSet(fused,CC.featextractors{1}.getLabels);
+        end
+        
+        function configInfo = getConfigInfo(CC)
+            configInfo = 'ChannelConcat';
+        end
+        
+                
+        function time = getTime(CC)
+            time = 0;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.dot b/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.dot
new file mode 100644
index 0000000..12c8d7e
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ChannelConcat -> ChannelConcat;
+
+  ChannelConcat [URL="ChannelConcat.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.html
new file mode 100644
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelConcat</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@ChannelConcat">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelConcat">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelConcat</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelConcat" border="2" style="color:#000;">  
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.map b/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/index.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/index.html
new file mode 100644
index 0000000..1460814
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelConcat/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@ChannelConcat</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@ChannelConcat">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@ChannelConcat">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@ChannelConcat</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ChannelConcat.html">ChannelConcat</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html
new file mode 100644
index 0000000..e649cb2
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html
@@ -0,0 +1,83 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ChannelRatio</title>
+  <meta name="keywords" content="ChannelRatio">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelRatio</a> &gt; ChannelRatio.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ChannelRatio
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelRatio.html" class="code" title="">ChannelRatio</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ChannelRatio.html" class="code" title="">ChannelRatio</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CR = ChannelRatio(CR)</a></li><li><a href="#_sub2" class="code">function CR = aggregate(CR)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CR)</a></li><li><a href="#_sub4" class="code">function time = getTime(CR)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ChannelRatio.m">ChannelRatio.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="ChannelRatio.html" class="code" title="">ChannelRatio</a> &lt; eegtoolkit.aggregation.AggregatorBase;
+0002     
+0003     properties
+0004     <span class="keyword">end</span>
+0005     
+0006     methods
+0007         
+0008         <a name="_sub0" href="#_subfunctions" class="code">function CR = ChannelRatio(CR)</a>
+0009         <span class="keyword">end</span>
+0010         
+0011         <a name="_sub1" href="#_subfunctions" class="code">function CR = aggregate(CR)</a>
+0012             numExtract = length(CR.featextractors);
+0013             <span class="keyword">if</span> numExtract ~=2
+0014                 error (<span class="string">'ChannelRatio: Number of transformers should be 2'</span>);
+0015             <span class="keyword">end</span>
+0016             in1 = CR.featextractors{1}.getInstances;
+0017             in2 = CR.featextractors{2}.getInstances;
+0018             ratio = in1./in2;
+0019             CR.instanceSet = eegtoolkit.util.InstanceSet(ratio,CR.featextractors{1}.getLabels);
+0020         <span class="keyword">end</span>
+0021         
+0022         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CR)</a>
+0023             configInfo = <span class="string">'ChannelRatio'</span>;
+0024         <span class="keyword">end</span>
+0025         
+0026                 
+0027         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(CR)</a>
+0028             time = 0;
+0029         <span class="keyword">end</span>
+0030     <span class="keyword">end</span>
+0031     
+0032 <span class="keyword">end</span>
+0033</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.m b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.m
new file mode 100644
index 0000000..3ac766a
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.m
@@ -0,0 +1,33 @@
+classdef ChannelRatio < eegtoolkit.aggregation.AggregatorBase;
+    
+    properties
+    end
+    
+    methods
+        
+        function CR = ChannelRatio(CR)
+        end
+        
+        function CR = aggregate(CR)
+            numExtract = length(CR.featextractors);
+            if numExtract ~=2
+                error ('ChannelRatio: Number of transformers should be 2');
+            end
+            in1 = CR.featextractors{1}.getInstances;
+            in2 = CR.featextractors{2}.getInstances;
+            ratio = in1./in2;
+            CR.instanceSet = eegtoolkit.util.InstanceSet(ratio,CR.featextractors{1}.getLabels);
+        end
+        
+        function configInfo = getConfigInfo(CR)
+            configInfo = 'ChannelRatio';
+        end
+        
+                
+        function time = getTime(CR)
+            time = 0;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.dot b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.dot
new file mode 100644
index 0000000..90f4631
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ChannelRatio -> ChannelRatio;
+
+  ChannelRatio [URL="ChannelRatio.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.html
new file mode 100644
index 0000000..afc5774
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelRatio</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@ChannelRatio">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelRatio">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelRatio</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelRatio" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ChannelRatio.html" title="ChannelRatio" alt="" coords="163,29,159,22,148,15,130,10,108,7,84,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,84,53,108,52,130,49,148,43,159,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.map b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.map
new file mode 100644
index 0000000..872ffb5
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="ChannelRatio.html" title="ChannelRatio" alt="" coords="163,29,159,22,148,15,130,10,108,7,84,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,84,53,108,52,130,49,148,43,159,37">
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/index.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/index.html
new file mode 100644
index 0000000..e3633bb
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@ChannelRatio</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@ChannelRatio">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@ChannelRatio">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@ChannelRatio</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ChannelRatio.html">ChannelRatio</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.html b/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.html
new file mode 100644
index 0000000..8e4d7ee
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.html
@@ -0,0 +1,147 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Fisher</title>
+  <meta name="keywords" content="Fisher">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@Fisher</a> &gt; Fisher.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Fisher
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Fisher.html" class="code" title="">Fisher</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Fisher.html" class="code" title="">Fisher</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function FA = Fisher(codebookfilename,pcanum)</a></li><li><a href="#_sub2" class="code">function FA = aggregate(FA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(FA)</a></li><li><a href="#_sub4" class="code">function time = getTime(FA)</a></li><li><a href="#_sub5" class="code">function [] = trainCodebook(session, channels, numCenters, codebookfilename,pcanum)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Fisher.m">Fisher.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Fisher.html" class="code" title="">Fisher</a> &lt; eegtoolkit.aggregation.AggregatorBase
+0002     properties
+0003         codebookInfo;
+0004         numClusters;
+0005         means;
+0006         covariances;
+0007         priors;
+0008         pcanum;
+0009     <span class="keyword">end</span>
+0010     
+0011     methods
+0012         <a name="_sub0" href="#_subfunctions" class="code">function FA = Fisher(codebookfilename,pcanum)</a>
+0013             load(codebookfilename);
+0014             FA.means = means;
+0015             FA.covariances = covariances;
+0016             FA.priors = priors;
+0017             FA.numClusters = length(priors);
+0018             FA.codebookInfo = codebookInfo;
+0019             FA.pcanum = pcanum;
+0020         <span class="keyword">end</span>
+0021         
+0022         <a name="_sub1" href="#_subfunctions" class="code">function FA = aggregate(FA)</a>
+0023             numExtract = length(FA.featextractors);
+0024             numFeatures = FA.featextractors{1}.instanceSet.getNumFeatures;
+0025             numTrials = length(FA.featextractors{1}.trials);
+0026             instances = zeros(numTrials,numExtract,numFeatures);
+0027             pcainstances = zeros(numTrials,numExtract,FA.pcanum);
+0028             <span class="keyword">if</span> FA.pcanum &gt; 0
+0029                 fishers = zeros(numTrials, FA.numClusters * FA.pcanum *2);
+0030             <span class="keyword">else</span>
+0031                 fishers = zeros(numTrials,FA.numClusters*numFeatures*2);
+0032             <span class="keyword">end</span>
+0033             <span class="keyword">for</span> i=1:numExtract
+0034                 instances(:,i,:) = FA.featextractors{i}.getInstances;
+0035                 <span class="keyword">if</span> FA.pcanum &gt; 0
+0036                     [~,pcainstances(:,i,:),~,~,~] = pca(squeeze(instances(:,i,:)),<span class="string">'NumComponents'</span>,FA.pcanum);
+0037                 <span class="keyword">end</span>
+0038             <span class="keyword">end</span>
+0039             <span class="keyword">for</span> i=1:numTrials
+0040                 <span class="keyword">if</span> FA.pcanum &gt; 0
+0041                     dataToBeEncoded = squeeze(pcainstances(i,:,:));
+0042                 <span class="keyword">else</span>
+0043                     dataToBeEncoded = squeeze(instances(i,:,:));
+0044                 <span class="keyword">end</span>
+0045                 fishers(i,:) =  vl_fisher(dataToBeEncoded', FA.means, FA.covariances, FA.priors);
+0046             <span class="keyword">end</span>
+0047             FA.instanceSet = eegtoolkit.util.InstanceSet(fishers,FA.featextractors{1}.getLabels);
+0048         <span class="keyword">end</span>
+0049         
+0050         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(FA)</a>
+0051             configInfo = sprintf(<span class="string">'Fisher:\tcodebook:%s'</span>,FA.codebookInfo);
+0052         <span class="keyword">end</span>
+0053                         
+0054         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(FA)</a>
+0055             time = 0;
+0056         <span class="keyword">end</span>
+0057     <span class="keyword">end</span>
+0058     
+0059     methods (Static)
+0060         <a name="_sub4" href="#_subfunctions" class="code">function [] = trainCodebook(session, channels, numCenters, codebookfilename,pcanum)</a>
+0061             nfft = 512;
+0062             extractors = {};
+0063             numChannels = length(channels);
+0064             numTrials = length(session.trials);
+0065             numFeatures = nfft/2+1;
+0066             instances = zeros(numTrials,numChannels,numFeatures);
+0067             h = waitbar(0,<span class="string">'message'</span>);
+0068             <span class="keyword">for</span> i=1:length(channels)
+0069                 waitbar(i/(length(channels)+10),h,sprintf(<span class="string">'Computing channel:%d'</span>,channels(i)));
+0070                 extractors{i} = eegtoolkit.featextraction.PWelch;
+0071                 extractors{i}.trials = session.trials;
+0072                 extractors{i}.channel = channels(i);
+0073                 extractors{i}.nfft = nfft;
+0074                 extractors{i}.seconds = 5;
+0075                 extractors{i}.extract;
+0076                 instances(:,i,:) = extractors{i}.getInstances;
+0077             <span class="keyword">end</span>
+0078             instances = reshape(instances,numTrials*numChannels,numFeatures);
+0079             waitbar(i/(length(channels)+10),h,<span class="string">'Computing gmm..'</span>);
+0080             <span class="keyword">if</span>(pcanum &gt; 0)
+0081                 [~,instances,~,~,~] = pca(instances,<span class="string">'NumComponents'</span>,pcanum);
+0082             <span class="keyword">end</span>
+0083             [means, covariances, priors] = vl_gmm(instances', numCenters);
+0084             waitbar(i+5/(length(channels)+10),h,<span class="string">'Saving variables..'</span>);
+0085             codebookInfo = sprintf(<span class="string">'filename:%s\tnumClusters:%d\tnumPCA:%d\tchannels:'</span>,codebookfilename, numCenters, pcanum);
+0086             <span class="keyword">for</span> i=1:length(channels)
+0087                 codebookInfo = sprintf(<span class="string">'%s%d '</span>,codebookInfo,channels(i));
+0088             <span class="keyword">end</span>
+0089             save(codebookfilename,<span class="string">'means'</span>,<span class="string">'covariances'</span>,<span class="string">'priors'</span>,<span class="string">'codebookInfo'</span>);
+0090             close(h);
+0091         <span class="keyword">end</span>
+0092         
+0093 
+0094     <span class="keyword">end</span>
+0095     
+0096 <span class="keyword">end</span>
+0097</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.m b/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.m
new file mode 100644
index 0000000..8c6ffe0
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.m
@@ -0,0 +1,97 @@
+classdef Fisher < eegtoolkit.aggregation.AggregatorBase
+    properties
+        codebookInfo;
+        numClusters;
+        means;
+        covariances;
+        priors;
+        pcanum;
+    end
+    
+    methods
+        function FA = Fisher(codebookfilename,pcanum)
+            load(codebookfilename);
+            FA.means = means;
+            FA.covariances = covariances;
+            FA.priors = priors;
+            FA.numClusters = length(priors);
+            FA.codebookInfo = codebookInfo;
+            FA.pcanum = pcanum;
+        end
+        
+        function FA = aggregate(FA)
+            numExtract = length(FA.featextractors);
+            numFeatures = FA.featextractors{1}.instanceSet.getNumFeatures;
+            numTrials = length(FA.featextractors{1}.trials);
+            instances = zeros(numTrials,numExtract,numFeatures);
+            pcainstances = zeros(numTrials,numExtract,FA.pcanum);
+            if FA.pcanum > 0
+                fishers = zeros(numTrials, FA.numClusters * FA.pcanum *2);
+            else
+                fishers = zeros(numTrials,FA.numClusters*numFeatures*2);
+            end
+            for i=1:numExtract
+                instances(:,i,:) = FA.featextractors{i}.getInstances;
+                if FA.pcanum > 0
+                    [~,pcainstances(:,i,:),~,~,~] = pca(squeeze(instances(:,i,:)),'NumComponents',FA.pcanum);
+                end
+            end
+            for i=1:numTrials
+                if FA.pcanum > 0
+                    dataToBeEncoded = squeeze(pcainstances(i,:,:));
+                else
+                    dataToBeEncoded = squeeze(instances(i,:,:));
+                end
+                fishers(i,:) =  vl_fisher(dataToBeEncoded', FA.means, FA.covariances, FA.priors);
+            end
+            FA.instanceSet = eegtoolkit.util.InstanceSet(fishers,FA.featextractors{1}.getLabels);
+        end
+        
+        function configInfo = getConfigInfo(FA)
+            configInfo = sprintf('Fisher:\tcodebook:%s',FA.codebookInfo);
+        end
+                        
+        function time = getTime(FA)
+            time = 0;
+        end
+    end
+    
+    methods (Static)
+        function [] = trainCodebook(session, channels, numCenters, codebookfilename,pcanum)
+            nfft = 512;
+            extractors = {};
+            numChannels = length(channels);
+            numTrials = length(session.trials);
+            numFeatures = nfft/2+1;
+            instances = zeros(numTrials,numChannels,numFeatures);
+            h = waitbar(0,'message');
+            for i=1:length(channels)
+                waitbar(i/(length(channels)+10),h,sprintf('Computing channel:%d',channels(i)));
+                extractors{i} = eegtoolkit.featextraction.PWelch;
+                extractors{i}.trials = session.trials;
+                extractors{i}.channel = channels(i);
+                extractors{i}.nfft = nfft;
+                extractors{i}.seconds = 5;
+                extractors{i}.extract;
+                instances(:,i,:) = extractors{i}.getInstances;
+            end
+            instances = reshape(instances,numTrials*numChannels,numFeatures);
+            waitbar(i/(length(channels)+10),h,'Computing gmm..');
+            if(pcanum > 0)
+                [~,instances,~,~,~] = pca(instances,'NumComponents',pcanum);
+            end
+            [means, covariances, priors] = vl_gmm(instances', numCenters);
+            waitbar(i+5/(length(channels)+10),h,'Saving variables..');
+            codebookInfo = sprintf('filename:%s\tnumClusters:%d\tnumPCA:%d\tchannels:',codebookfilename, numCenters, pcanum);
+            for i=1:length(channels)
+                codebookInfo = sprintf('%s%d ',codebookInfo,channels(i));
+            end
+            save(codebookfilename,'means','covariances','priors','codebookInfo');
+            close(h);
+        end
+        
+
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/graph.dot b/doc/+eegtoolkit/+aggregation/@Fisher/graph.dot
new file mode 100644
index 0000000..b9da3e5
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Fisher -> Fisher;
+
+  Fisher [URL="Fisher.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/graph.html b/doc/+eegtoolkit/+aggregation/@Fisher/graph.html
new file mode 100644
index 0000000..51a136b
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@Fisher</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@Fisher">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@Fisher">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@Fisher</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@Fisher" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Fisher.html" title="Fisher" alt="" coords="91,29,89,22,83,15,73,10,61,7,48,5,35,7,23,10,13,15,7,22,5,29,7,37,13,43,23,49,35,52,48,53,61,52,73,49,83,43,89,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/graph.map b/doc/+eegtoolkit/+aggregation/@Fisher/graph.map
new file mode 100644
index 0000000..09f0a4e
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/index.html b/doc/+eegtoolkit/+aggregation/@Fisher/index.html
new file mode 100644
index 0000000..cde5909
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@Fisher/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@Fisher</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@Fisher">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@Fisher">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@Fisher</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Fisher.html">Fisher</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.html b/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.html
new file mode 100644
index 0000000..a1115e5
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.html
@@ -0,0 +1,81 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of LateFusion</title>
+  <meta name="keywords" content="LateFusion">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@LateFusion</a> &gt; LateFusion.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>LateFusion
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LateFusion.html" class="code" title="">LateFusion</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LateFusion.html" class="code" title="">LateFusion</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function LFA = LateFusion(LFA)</a></li><li><a href="#_sub2" class="code">function LFA = aggregate(LFA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(LFA)</a></li><li><a href="#_sub4" class="code">function time = getTime(LFA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="LateFusion.m">LateFusion.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="LateFusion.html" class="code" title="">LateFusion</a> &lt; eegtoolkit.aggregation.AggregatorBase;
+0002     
+0003     properties
+0004     <span class="keyword">end</span>
+0005     
+0006     methods
+0007         
+0008         <a name="_sub0" href="#_subfunctions" class="code">function LFA = LateFusion(LFA)</a>
+0009         <span class="keyword">end</span>
+0010         
+0011         <a name="_sub1" href="#_subfunctions" class="code">function LFA = aggregate(LFA)</a>
+0012             numTransf = length(LFA.featextractors);
+0013             LFA.instanceSet = eegtoolkit.util.FusionInstanceSet(LFA.featextractors{1}.instanceSet);
+0014             
+0015             <span class="keyword">for</span> i=1:numTransf
+0016                 LFA.instanceSet = LFA.instanceSet.addInstanceSet(LFA.featextractors{i}.instanceSet);
+0017             <span class="keyword">end</span>
+0018         <span class="keyword">end</span>
+0019         
+0020         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(LFA)</a>
+0021             configInfo = <span class="string">'LateFusion'</span>;
+0022         <span class="keyword">end</span>
+0023         
+0024                 
+0025         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(LFA)</a>
+0026             time = 0;
+0027         <span class="keyword">end</span>
+0028     <span class="keyword">end</span>
+0029     
+0030 <span class="keyword">end</span>
+0031</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.m b/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.m
new file mode 100644
index 0000000..c3aa6c7
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.m
@@ -0,0 +1,31 @@
+classdef LateFusion < eegtoolkit.aggregation.AggregatorBase;
+    
+    properties
+    end
+    
+    methods
+        
+        function LFA = LateFusion(LFA)
+        end
+        
+        function LFA = aggregate(LFA)
+            numTransf = length(LFA.featextractors);
+            LFA.instanceSet = eegtoolkit.util.FusionInstanceSet(LFA.featextractors{1}.instanceSet);
+            
+            for i=1:numTransf
+                LFA.instanceSet = LFA.instanceSet.addInstanceSet(LFA.featextractors{i}.instanceSet);
+            end
+        end
+        
+        function configInfo = getConfigInfo(LFA)
+            configInfo = 'LateFusion';
+        end
+        
+                
+        function time = getTime(LFA)
+            time = 0;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/graph.dot b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.dot
new file mode 100644
index 0000000..41a4220
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  LateFusion -> LateFusion;
+
+  LateFusion [URL="LateFusion.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/graph.html b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.html
new file mode 100644
index 0000000..42fda6d
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@LateFusion</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@LateFusion">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@LateFusion">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@LateFusion</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@LateFusion" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="LateFusion.html" title="LateFusion" alt="" coords="139,29,135,22,126,15,111,10,93,7,72,5,51,7,33,10,18,15,9,22,5,29,9,37,18,43,33,49,51,52,72,53,93,52,111,49,126,43,135,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/graph.map b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.map
new file mode 100644
index 0000000..ab3767d
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/index.html b/doc/+eegtoolkit/+aggregation/@LateFusion/index.html
new file mode 100644
index 0000000..6b955cc
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@LateFusion/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
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+  <title>Index for Directory ./+eegtoolkit/+aggregation/@LateFusion</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@LateFusion">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@LateFusion">
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+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@LateFusion</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="LateFusion.html">LateFusion</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html b/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html
new file mode 100644
index 0000000..9b3acf6
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html
@@ -0,0 +1,133 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of VLAD</title>
+  <meta name="keywords" content="VLAD">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@VLAD</a> &gt; VLAD.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>VLAD
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="VLAD.html" class="code" title="">VLAD</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="VLAD.html" class="code" title="">VLAD</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function VA = VLAD(codebookfilename)</a></li><li><a href="#_sub2" class="code">function VA = aggregate(VA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(VA)</a></li><li><a href="#_sub4" class="code">function time = getTime(VA)</a></li><li><a href="#_sub5" class="code">function [] = trainCodebook(session, channels, numCenters, codebookfilename)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="VLAD.m">VLAD.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="VLAD.html" class="code" title="">VLAD</a> &lt; eegtoolkit.aggregation.AggregatorBase;
+0002     
+0003     properties
+0004         kdtree;
+0005         centers;
+0006         codebookInfo;
+0007         numClusters;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods
+0011         
+0012         <a name="_sub0" href="#_subfunctions" class="code">function VA = VLAD(codebookfilename)</a>
+0013             load(codebookfilename);
+0014             VA.kdtree = kdtree;
+0015             VA.centers = centers;
+0016             VA.codebookInfo = codebookInfo;
+0017             [~,VA.numClusters] = size(centers);
+0018         <span class="keyword">end</span>
+0019         
+0020         <a name="_sub1" href="#_subfunctions" class="code">function VA = aggregate(VA)</a>
+0021             numExtract = length(VA.transformers);
+0022             numFeatures = VA.featextractors{1}.instanceSet.getNumFeatures;
+0023             numTrials = length(VA.featextractors{1}.trials);
+0024             instances = zeros(numTrials,numExtract,numFeatures);
+0025             vlads = zeros(numTrials,VA.kdtree.numData*numFeatures);
+0026             <span class="keyword">for</span> i=1:numExtract
+0027                 instances(:,i,:) = VA.featextractors{i}.getInstances;
+0028             <span class="keyword">end</span>
+0029             <span class="keyword">for</span> i=1:numTrials
+0030                 dataToBeEncoded = squeeze(instances(i,:,:));
+0031                 nn = vl_kdtreequery(VA.kdtree, VA.centers, dataToBeEncoded');
+0032                 assignments = zeros(VA.numClusters, numExtract);
+0033                 assignments(sub2ind(size(assignments), nn, 1:length(nn))) = 1;
+0034                 vlads(i,:) = vl_vlad(dataToBeEncoded',VA.centers,assignments);
+0035             <span class="keyword">end</span>
+0036             VA.instanceSet = eegtoolkit.util.InstanceSet(vlads,VA.featextractors{1}.getLabels);
+0037         <span class="keyword">end</span>
+0038         
+0039         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(VA)</a>
+0040             configInfo = sprintf(<span class="string">'VLAD:\tcodebook:%s'</span>,VA.codebookInfo);
+0041         <span class="keyword">end</span>
+0042         
+0043                 
+0044         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(VA)</a>
+0045             time = 0;
+0046         <span class="keyword">end</span>
+0047     <span class="keyword">end</span>
+0048     
+0049     methods (Static)
+0050         <a name="_sub4" href="#_subfunctions" class="code">function [] = trainCodebook(session, channels, numCenters, codebookfilename)</a>
+0051             nfft = 512;
+0052             extractors = {};
+0053             numChannels = length(channels);
+0054             numTrials = length(session.trials);
+0055             numFeatures = nfft/2+1;
+0056             instances = zeros(numTrials,numChannels,numFeatures);
+0057             h = waitbar(0,<span class="string">'message'</span>);
+0058             <span class="keyword">for</span> i=1:length(channels)
+0059                 waitbar(i/(length(channels)+10),h,sprintf(<span class="string">'Computing channel:%d'</span>,channels(i)));
+0060                 extractors{i} = eegtoolkit.transformer.PWelchTransformer;
+0061                 extractors{i}.trials = session.trials;
+0062                 extractors{i}.channel = channels(i);
+0063                 extractors{i}.nfft = nfft;
+0064                 extractors{i}.seconds = 5;
+0065                 extractors{i}.transform;
+0066                 instances(:,i,:) = extractors{i}.getInstances;
+0067             <span class="keyword">end</span>
+0068             instances = reshape(instances,numTrials*numChannels,numFeatures);
+0069             waitbar(i/(length(channels)+10),h,<span class="string">'Clustering..'</span>);
+0070             centers = vl_kmeans(instances',numCenters);
+0071             waitbar(i+4/(length(channels)+10),h,<span class="string">'Building kdtree..'</span>);
+0072             kdtree = vl_kdtreebuild(centers);
+0073             waitbar(i+5/(length(channels)+10),h,<span class="string">'Saving variables..'</span>);
+0074             codebookInfo = sprintf(<span class="string">'filename:%s\tnumClusters:%d\tchannels:'</span>,codebookfilename, numCenters);
+0075             <span class="keyword">for</span> i=1:length(channels)
+0076                 codebookInfo = sprintf(<span class="string">'%s%d '</span>,codebookInfo,channels(i));
+0077             <span class="keyword">end</span>
+0078             save(codebookfilename,<span class="string">'centers'</span>,<span class="string">'kdtree'</span>,<span class="string">'codebookInfo'</span>);
+0079             close(h);
+0080         <span class="keyword">end</span>
+0081     <span class="keyword">end</span>
+0082 <span class="keyword">end</span>
+0083</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.m b/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.m
new file mode 100644
index 0000000..7657d89
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.m
@@ -0,0 +1,83 @@
+classdef VLAD < eegtoolkit.aggregation.AggregatorBase;
+    
+    properties
+        kdtree;
+        centers;
+        codebookInfo;
+        numClusters;
+    end
+    
+    methods
+        
+        function VA = VLAD(codebookfilename)
+            load(codebookfilename);
+            VA.kdtree = kdtree;
+            VA.centers = centers;
+            VA.codebookInfo = codebookInfo;
+            [~,VA.numClusters] = size(centers);
+        end
+        
+        function VA = aggregate(VA)
+            numExtract = length(VA.transformers);
+            numFeatures = VA.featextractors{1}.instanceSet.getNumFeatures;
+            numTrials = length(VA.featextractors{1}.trials);
+            instances = zeros(numTrials,numExtract,numFeatures);
+            vlads = zeros(numTrials,VA.kdtree.numData*numFeatures);
+            for i=1:numExtract
+                instances(:,i,:) = VA.featextractors{i}.getInstances;
+            end
+            for i=1:numTrials
+                dataToBeEncoded = squeeze(instances(i,:,:));
+                nn = vl_kdtreequery(VA.kdtree, VA.centers, dataToBeEncoded');
+                assignments = zeros(VA.numClusters, numExtract);
+                assignments(sub2ind(size(assignments), nn, 1:length(nn))) = 1;
+                vlads(i,:) = vl_vlad(dataToBeEncoded',VA.centers,assignments);
+            end
+            VA.instanceSet = eegtoolkit.util.InstanceSet(vlads,VA.featextractors{1}.getLabels);
+        end
+        
+        function configInfo = getConfigInfo(VA)
+            configInfo = sprintf('VLAD:\tcodebook:%s',VA.codebookInfo);
+        end
+        
+                
+        function time = getTime(VA)
+            time = 0;
+        end
+    end
+    
+    methods (Static)
+        function [] = trainCodebook(session, channels, numCenters, codebookfilename)
+            nfft = 512;
+            extractors = {};
+            numChannels = length(channels);
+            numTrials = length(session.trials);
+            numFeatures = nfft/2+1;
+            instances = zeros(numTrials,numChannels,numFeatures);
+            h = waitbar(0,'message');
+            for i=1:length(channels)
+                waitbar(i/(length(channels)+10),h,sprintf('Computing channel:%d',channels(i)));
+                extractors{i} = eegtoolkit.transformer.PWelchTransformer;
+                extractors{i}.trials = session.trials;
+                extractors{i}.channel = channels(i);
+                extractors{i}.nfft = nfft;
+                extractors{i}.seconds = 5;
+                extractors{i}.transform;
+                instances(:,i,:) = extractors{i}.getInstances;
+            end
+            instances = reshape(instances,numTrials*numChannels,numFeatures);
+            waitbar(i/(length(channels)+10),h,'Clustering..');
+            centers = vl_kmeans(instances',numCenters);
+            waitbar(i+4/(length(channels)+10),h,'Building kdtree..');
+            kdtree = vl_kdtreebuild(centers);
+            waitbar(i+5/(length(channels)+10),h,'Saving variables..');
+            codebookInfo = sprintf('filename:%s\tnumClusters:%d\tchannels:',codebookfilename, numCenters);
+            for i=1:length(channels)
+                codebookInfo = sprintf('%s%d ',codebookInfo,channels(i));
+            end
+            save(codebookfilename,'centers','kdtree','codebookInfo');
+            close(h);
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/graph.dot b/doc/+eegtoolkit/+aggregation/@VLAD/graph.dot
new file mode 100644
index 0000000..a7489f3
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  VLAD -> VLAD;
+
+  VLAD [URL="VLAD.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/graph.html b/doc/+eegtoolkit/+aggregation/@VLAD/graph.html
new file mode 100644
index 0000000..09f3963
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@VLAD</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@VLAD">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@VLAD">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@VLAD</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@VLAD" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="VLAD.html" title="VLAD" alt="" coords="99,29,97,22,90,15,80,10,66,7,52,5,38,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,38,52,52,53,66,52,80,49,90,43,97,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/graph.map b/doc/+eegtoolkit/+aggregation/@VLAD/graph.map
new file mode 100644
index 0000000..06ab2bd
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="VLAD.html" title="VLAD" alt="" coords="99,29,97,22,90,15,80,10,66,7,52,5,38,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,38,52,52,53,66,52,80,49,90,43,97,37">
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/graph.png b/doc/+eegtoolkit/+aggregation/@VLAD/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/index.html b/doc/+eegtoolkit/+aggregation/@VLAD/index.html
new file mode 100644
index 0000000..8b28ee2
--- /dev/null
+++ b/doc/+eegtoolkit/+aggregation/@VLAD/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+aggregation/@VLAD</title>
+  <meta name="keywords" content="./+eegtoolkit/+aggregation/@VLAD">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@VLAD">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+aggregation/@VLAD</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="VLAD.html">VLAD</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html
new file mode 100644
index 0000000..27f3d17
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html
@@ -0,0 +1,181 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Adaboost</title>
+  <meta name="keywords" content="Adaboost">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@Adaboost</a> &gt; Adaboost.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Adaboost
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Adaboost.html" class="code" title="">Adaboost</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Adaboost.html" class="code" title="">Adaboost</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function BOOST = Adaboost(instanceSet, Method, NLearn, Learners)</a></li><li><a href="#_sub2" class="code">function BOOST = build(BOOST)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(BOOST,instance)</a></li><li><a href="#_sub4" class="code">function BOOST = reset(BOOST)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(BOOST)</a></li><li><a href="#_sub6" class="code">function time = getTime(BOOST)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Adaboost.m">Adaboost.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Adaboost.html" class="code" title="">Adaboost</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008         Method <span class="comment">% AdaboostM2 (default), TotalBoost, LPBoost, Subspace, etc</span>
+0009         NLearn <span class="comment">% Number of learners (default 100)</span>
+0010         Learners <span class="comment">% Tree (default), KNN (only for Subspace), Discriminant(recommended for subspace), Custom</span>
+0011         models;
+0012         totalTime;
+0013         totalCount;
+0014     <span class="keyword">end</span>
+0015     
+0016     methods (Access = public)
+0017         <a name="_sub0" href="#_subfunctions" class="code">function BOOST = Adaboost(instanceSet, Method, NLearn, Learners)</a>
+0018             <span class="comment">%set default parameters</span>
+0019             BOOST.Method = <span class="string">'AdaBoostM2'</span>;
+0020             BOOST.NLearn=100;
+0021             BOOST.Learners = <span class="string">'Tree'</span>;
+0022             <span class="keyword">if</span> nargin &gt; 0
+0023                 BOOST.instanceSet = instanceSet;
+0024             <span class="keyword">end</span>
+0025             <span class="keyword">if</span> nargin &gt; 1
+0026                 BOOST.Method = Method;
+0027             <span class="keyword">end</span>
+0028             <span class="keyword">if</span> nargin &gt; 2 
+0029                 BOOST.NLearn=NLearn;
+0030             <span class="keyword">end</span>
+0031             <span class="keyword">if</span> nargin &gt; 3
+0032                 BOOST.Learners = Learners;
+0033             <span class="keyword">end</span>
+0034             BOOST.totalTime = 0;
+0035             BOOST.totalCount = 0;
+0036         <span class="keyword">end</span>
+0037         
+0038         <a name="_sub1" href="#_subfunctions" class="code">function BOOST = build(BOOST)</a>
+0039             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0040             BOOST.reset;
+0041             numLabels = BOOST.instanceSet.getNumLabels;
+0042             uniqueLabels = unique(BOOST.instanceSet.getLabels);
+0043             
+0044             <span class="comment">% ---- Multi-Class ----- %</span>
+0045             instances=BOOST.instanceSet.instances;
+0046             labels=BOOST.instanceSet.labels;
+0047             
+0048             BOOST.models{1} = fitensemble(instances,labels,BOOST.Method, BOOST.NLearn, BOOST.Learners,<span class="keyword">...</span>
+0049                 <span class="string">'Type'</span>,<span class="string">'Classification'</span>);
+0050 
+0051 <span class="comment">%             for i=1:numLabels</span>
+0052 <span class="comment">%                 currentLabel = uniqueLabels(i);</span>
+0053 <span class="comment">%                 labels = zeros(BOOST.instanceSet.getNumInstances,1)-1;</span>
+0054 <span class="comment">%                 labels(BOOST.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;</span>
+0055 <span class="comment">%                 instances = sparse(BOOST.instanceSet.getInstances);</span>
+0056 <span class="comment">%                 N = length(labels); % X training labels</span>
+0057 <span class="comment">%                 W = 1/N * ones(N,1); %Weights initialization</span>
+0058 <span class="comment">%                 M = 10; % Number of boosting iterations</span>
+0059 <span class="comment">%                 for m=1:M</span>
+0060 <span class="comment">%                     C = 1; %The cost parameters of the linear SVM, you can...</span>
+0061 <span class="comment">%                     % perform a grid search for the optimal value as well</span>
+0062 <span class="comment">%</span>
+0063 <span class="comment">%                     %Calculate the error and alpha in adaBoost with cross validation</span>
+0064 <span class="comment">%                     cmd = ['-c ', num2str(C), ' -b 1'];</span>
+0065 <span class="comment">%                     model = svmtrain(W,labels, instances, cmd);</span>
+0066 <span class="comment">%                     [Xout, acc, ~] = svmpredict(labels, instances,model);</span>
+0067 <span class="comment">%</span>
+0068 <span class="comment">%                     err = sum(.5 * W .* acc * N)/sum(W);</span>
+0069 <span class="comment">%                     alpha = log( (1-err)/err );</span>
+0070 <span class="comment">%</span>
+0071 <span class="comment">%                     % update the weight</span>
+0072 <span class="comment">%                     W = W.*exp( - alpha.*Xout.*X );</span>
+0073 <span class="comment">%                     W = W/norm(W);</span>
+0074 <span class="comment">%                 end</span>
+0075 <span class="comment">%                 BOOST.models{i} = model;</span>
+0076 <span class="comment">%</span>
+0077 <span class="comment">%             end</span>
+0078             
+0079         <span class="keyword">end</span>
+0080         
+0081         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(BOOST,instance)</a>
+0082             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0083             <span class="comment">%output = predicted class</span>
+0084             <span class="comment">%probabilities = probability for predicted class</span>
+0085             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0086             
+0087             
+0088             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0089             numModels = length(BOOST.models);
+0090             [numinstance, ~] = size(instance);
+0091             scores = zeros(numModels,numinstance);
+0092              
+0093             <span class="comment">% ---- Multi-class ----- %</span>
+0094             tic
+0095             [label,scores] = predict(BOOST.models{1},instance); 
+0096             BOOST.totalTime = BOOST.totalTime + toc;
+0097             BOOST.totalCount = BOOST.totalCount + numinstance;
+0098 
+0099              output = zeros(numinstance,1);
+0100              probabilities = zeros(numinstance,1);
+0101              <span class="comment">%we need these for ranking metrics (e.g. mAP)</span>
+0102              ranking = scores;
+0103              <span class="keyword">for</span> i=1:numinstance
+0104                  <span class="comment">%select the class with the highest probability</span>
+0105                  [prob, idx] = max(scores(i,:));
+0106                  uniqueLabels = unique(BOOST.instanceSet.getLabels);
+0107                  <span class="comment">%output the label with highest probability</span>
+0108                  output(i,1) = uniqueLabels(idx);
+0109                  <span class="comment">%return the probability for the output label</span>
+0110                  probabilities(i,1) = prob;
+0111              <span class="keyword">end</span>
+0112         <span class="keyword">end</span>
+0113         
+0114         <a name="_sub3" href="#_subfunctions" class="code">function BOOST = reset(BOOST)</a>
+0115             <span class="comment">%delete all stored models</span>
+0116             BOOST.models = {};
+0117         <span class="keyword">end</span>
+0118         
+0119         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(BOOST)</a>
+0120             configInfo = sprintf(<span class="string">'Adaboost: Method: %s NLearn: %d Learners: %s'</span>,<span class="keyword">...</span>
+0121                 BOOST.Method, BOOST.NLearn, BOOST.Learners);
+0122         <span class="keyword">end</span>
+0123         
+0124                         
+0125         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(BOOST)</a>
+0126             time = BOOST.totalTime / BOOST.totalCount;
+0127         <span class="keyword">end</span>
+0128                 
+0129     <span class="keyword">end</span>
+0130 <span class="keyword">end</span>
+0131</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.m b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.m
new file mode 100644
index 0000000..cd27623
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.m
@@ -0,0 +1,131 @@
+classdef Adaboost < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties
+        Method % AdaboostM2 (default), TotalBoost, LPBoost, Subspace, etc
+        NLearn % Number of learners (default 100)
+        Learners % Tree (default), KNN (only for Subspace), Discriminant(recommended for subspace), Custom
+        models;
+        totalTime;
+        totalCount;
+    end
+    
+    methods (Access = public)
+        function BOOST = Adaboost(instanceSet, Method, NLearn, Learners)
+            %set default parameters
+            BOOST.Method = 'AdaBoostM2';
+            BOOST.NLearn=100;
+            BOOST.Learners = 'Tree';
+            if nargin > 0
+                BOOST.instanceSet = instanceSet;
+            end
+            if nargin > 1
+                BOOST.Method = Method;
+            end
+            if nargin > 2 
+                BOOST.NLearn=NLearn;
+            end
+            if nargin > 3
+                BOOST.Learners = Learners;
+            end
+            BOOST.totalTime = 0;
+            BOOST.totalCount = 0;
+        end
+        
+        function BOOST = build(BOOST)
+            %clear all from previous calls to "build"
+            BOOST.reset;
+            numLabels = BOOST.instanceSet.getNumLabels;
+            uniqueLabels = unique(BOOST.instanceSet.getLabels);
+            
+            % ---- Multi-Class ----- %
+            instances=BOOST.instanceSet.instances;
+            labels=BOOST.instanceSet.labels;
+            
+            BOOST.models{1} = fitensemble(instances,labels,BOOST.Method, BOOST.NLearn, BOOST.Learners,...
+                'Type','Classification');
+
+%             for i=1:numLabels
+%                 currentLabel = uniqueLabels(i);
+%                 labels = zeros(BOOST.instanceSet.getNumInstances,1)-1;
+%                 labels(BOOST.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+%                 instances = sparse(BOOST.instanceSet.getInstances);
+%                 N = length(labels); % X training labels
+%                 W = 1/N * ones(N,1); %Weights initialization
+%                 M = 10; % Number of boosting iterations
+%                 for m=1:M
+%                     C = 1; %The cost parameters of the linear SVM, you can...
+%                     % perform a grid search for the optimal value as well
+%                     
+%                     %Calculate the error and alpha in adaBoost with cross validation
+%                     cmd = ['-c ', num2str(C), ' -b 1'];
+%                     model = svmtrain(W,labels, instances, cmd);
+%                     [Xout, acc, ~] = svmpredict(labels, instances,model);
+%                     
+%                     err = sum(.5 * W .* acc * N)/sum(W);
+%                     alpha = log( (1-err)/err );
+%                     
+%                     % update the weight
+%                     W = W.*exp( - alpha.*Xout.*X );
+%                     W = W/norm(W);
+%                 end
+%                 BOOST.models{i} = model;
+%                 
+%             end
+            
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(BOOST,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(BOOST.models);
+            [numinstance, ~] = size(instance);
+            scores = zeros(numModels,numinstance);
+             
+            % ---- Multi-class ----- %
+            tic
+            [label,scores] = predict(BOOST.models{1},instance); 
+            BOOST.totalTime = BOOST.totalTime + toc;
+            BOOST.totalCount = BOOST.totalCount + numinstance;
+
+             output = zeros(numinstance,1);
+             probabilities = zeros(numinstance,1);
+             %we need these for ranking metrics (e.g. mAP)
+             ranking = scores;
+             for i=1:numinstance
+                 %select the class with the highest probability
+                 [prob, idx] = max(scores(i,:));
+                 uniqueLabels = unique(BOOST.instanceSet.getLabels);
+                 %output the label with highest probability
+                 output(i,1) = uniqueLabels(idx);
+                 %return the probability for the output label
+                 probabilities(i,1) = prob;
+             end
+        end
+        
+        function BOOST = reset(BOOST)
+            %delete all stored models
+            BOOST.models = {};
+        end
+        
+        function configInfo = getConfigInfo(BOOST)
+            configInfo = sprintf('Adaboost: Method: %s NLearn: %d Learners: %s',...
+                BOOST.Method, BOOST.NLearn, BOOST.Learners);
+        end
+        
+                        
+        function time = getTime(BOOST)
+            time = BOOST.totalTime / BOOST.totalCount;
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@Adaboost/graph.dot b/doc/+eegtoolkit/+classification/@Adaboost/graph.dot
new file mode 100644
index 0000000..3b7d0bf
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@Adaboost/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Adaboost -> Adaboost;
+
+  Adaboost [URL="Adaboost.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@Adaboost/graph.html b/doc/+eegtoolkit/+classification/@Adaboost/graph.html
new file mode 100644
index 0000000..3ed3a88
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@Adaboost/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@Adaboost</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@Adaboost">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@Adaboost">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@Adaboost</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@Adaboost" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Adaboost.html" title="Adaboost" alt="" coords="123,29,120,22,112,15,99,10,82,7,64,5,46,7,29,10,16,15,8,22,5,29,8,37,16,43,29,49,46,52,64,53,82,52,99,49,112,43,120,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@Adaboost/graph.map b/doc/+eegtoolkit/+classification/@Adaboost/graph.map
new file mode 100644
index 0000000..7cb3dd1
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@Adaboost/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="Adaboost.html" title="Adaboost" alt="" coords="123,29,120,22,112,15,99,10,82,7,64,5,46,7,29,10,16,15,8,22,5,29,8,37,16,43,29,49,46,52,64,53,82,52,99,49,112,43,120,37">
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diff --git a/doc/+eegtoolkit/+classification/@Adaboost/index.html b/doc/+eegtoolkit/+classification/@Adaboost/index.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@Adaboost</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Adaboost.html">Adaboost</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html
new file mode 100644
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--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html
@@ -0,0 +1,183 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of CSPWrapper</title>
+  <meta name="keywords" content="CSPWrapper">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@CSPWrapper</a> &gt; CSPWrapper.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>CSPWrapper
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CSPWrapper.html" class="code" title="">CSPWrapper</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CSPWrapper.html" class="code" title="">CSPWrapper</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CSP = CSPWrapper(instanceSet)</a></li><li><a href="#_sub2" class="code">function CSP = build(CSP)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(CSP,instance)</a></li><li><a href="#_sub4" class="code">function CSP = reset(CSP)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(CSP)</a></li><li><a href="#_sub6" class="code">function time = getTime(CSP)</a></li><li><a href="#_sub7" class="code">function [] = learnCSPMatrix(CSP, sMatrix, labels)</a></li><li><a href="#_sub8" class="code">function instances = extract(CSP,sMatrix)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="CSPWrapper.m">CSPWrapper.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="CSPWrapper.html" class="code" title="">CSPWrapper</a> &lt; eegtoolkit.classification.ClassifierBase;
+0002     properties (Constant)
+0003         
+0004     <span class="keyword">end</span>
+0005     properties
+0006         baseClassifier;
+0007         channel;
+0008         cspFilter;
+0009     <span class="keyword">end</span>
+0010     
+0011     methods (Access = public)
+0012         <a name="_sub0" href="#_subfunctions" class="code">function CSP = CSPWrapper(instanceSet)</a>
+0013 <span class="comment">%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')</span>
+0014 <span class="comment">%                 CSP.instanceSet = instanceSet;</span>
+0015 <span class="comment">%             else</span>
+0016 <span class="comment">%                 error('RawSignal extractor should be used with CSPWrapper');</span>
+0017 <span class="comment">%             end</span>
+0018         <span class="keyword">end</span>
+0019         
+0020         
+0021         <a name="_sub1" href="#_subfunctions" class="code">function CSP = build(CSP)</a>
+0022             <span class="comment">% Builds the classification models</span>
+0023             CSP.learnCSPMatrix(CSP.instanceSet.sMatrix,CSP.instanceSet.labels);
+0024             instanceLocal = CSP.extract(CSP.instanceSet.sMatrix);
+0025             CSP.baseClassifier.instanceSet = eegtoolkit.util.InstanceSet(instanceLocal,CSP.instanceSet.labels);
+0026             CSP.baseClassifier.build;
+0027             CSP.reset;
+0028         <span class="keyword">end</span>
+0029         
+0030         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(CSP,instance)</a>
+0031 <span class="comment">%             instance = CSP.extract</span>
+0032             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0033             <span class="comment">%output = predicted class</span>
+0034             <span class="comment">%probabilities = probability for predicted class</span>
+0035             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0036             
+0037             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0038             testInstances = CSP.extract(instance);
+0039             [output, probabilities, ranking] = CSP.baseClassifier.classifyInstance(testInstances);
+0040 <span class="comment">%             numModels = length(LSVM.models);</span>
+0041 <span class="comment">%             [numinstance, ~] = size(testInstances);</span>
+0042 <span class="comment">%             scores = zeros(numModels,numinstance);</span>
+0043 <span class="comment">%             for i=1:numModels</span>
+0044 <span class="comment">%                 %predict using the stored models</span>
+0045 <span class="comment">%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');</span>
+0046 <span class="comment">%                 %store probability for each class</span>
+0047 <span class="comment">%                 scores(i,:) = t(:,1);</span>
+0048 <span class="comment">%             end</span>
+0049 <span class="comment">%             output = zeros(numinstance,1);</span>
+0050 <span class="comment">%             probabilities = zeros(numinstance,1);</span>
+0051 <span class="comment">%             ranking = scores;</span>
+0052 <span class="comment">%             for i=1:numinstance</span>
+0053 <span class="comment">%                 %select the class with the highest probability</span>
+0054 <span class="comment">%                 [prob, idx] = max(scores(:,i));</span>
+0055 <span class="comment">%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);</span>
+0056 <span class="comment">%                 %output the label with highest probability</span>
+0057 <span class="comment">%                 output(i,1) = uniqueLabels(idx);</span>
+0058 <span class="comment">%                 %return the probability for the output label</span>
+0059 <span class="comment">%                 probabilities(i,1) = prob;</span>
+0060 <span class="comment">%             end</span>
+0061         <span class="keyword">end</span>
+0062         
+0063         <a name="_sub3" href="#_subfunctions" class="code">function CSP = reset(CSP)</a>
+0064             <span class="comment">% 'Resets' the classifier.</span>
+0065 <span class="comment">%             CSP.models = {};</span>
+0066         <span class="keyword">end</span>
+0067         
+0068         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CSP)</a>
+0069             configInfo = <span class="string">'\n'</span>;
+0070         <span class="keyword">end</span>
+0071         
+0072                         
+0073         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(CSP)</a>
+0074             time = 0;
+0075         <span class="keyword">end</span>
+0076     <span class="keyword">end</span>
+0077     methods (Access = private)
+0078         <a name="_sub6" href="#_subfunctions" class="code">function [] = learnCSPMatrix(CSP, sMatrix, labels)</a>
+0079             [numTrials,numChannels,~] = size(sMatrix);
+0080 <span class="comment">%             labels = CSP.instanceSet.getLabels;</span>
+0081 <span class="comment">%             sMatrix = permute(sMatrix,[2,3,1]);</span>
+0082 <span class="comment">%             sMatrix = permute(sMatrix,[2 1 3]);</span>
+0083             sMatrix = permute(sMatrix,[3,2,1]);
+0084             <span class="keyword">for</span> i=1:numChannels
+0085                 <span class="keyword">for</span> j=1:numTrials
+0086                     sMatrix(:,i,j) = (sMatrix(:,i,j) - mean(sMatrix(:,i,j)));
+0087                 <span class="keyword">end</span>
+0088             <span class="keyword">end</span>
+0089             trialCov = zeros(numChannels,numChannels,numTrials);
+0090             <span class="keyword">for</span> t=1:length(labels)
+0091                 E = sMatrix(:,:,t)';
+0092                 EE = E * E';
+0093                 trialCov(:,:,t) = EE ./trace(EE);
+0094             <span class="keyword">end</span>
+0095             <span class="comment">%TODO: works only for 2 labels, [1,2]</span>
+0096             <span class="keyword">for</span> c=1:2
+0097                 covMat{c} = mean(trialCov(:,:,labels == c),3);
+0098             <span class="keyword">end</span>
+0099             [U, D] = eig(covMat{1},covMat{2},<span class="string">'qz'</span>);
+0100             eigenvalues = diag(D);
+0101             [~,ind] = sort(eigenvalues,<span class="string">'descend'</span>);
+0102             U = U(:,ind);
+0103             CSP.cspFilter = U';
+0104 <span class="comment">%             for i=1:size(sMatrix,3);</span>
+0105 <span class="comment">%                 sMatrix(:,:,i) = (cspFilter*sMatrix(:,:,i)')';</span>
+0106 <span class="comment">%             end</span>
+0107 <span class="comment">%             instances = zeros(numTrials,numChannels);</span>
+0108 <span class="comment">%             for i=1:numTrials</span>
+0109 <span class="comment">%                 projectedTrial = sMatrix(:,:,i);</span>
+0110 <span class="comment">%                 variances = var(projectedTrial,0,1);</span>
+0111 <span class="comment">%                 instances(i,:) = log(variances)';</span>
+0112 <span class="comment">%             end</span>
+0113 <span class="comment">%             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);</span>
+0114         <span class="keyword">end</span>
+0115         
+0116         <a name="_sub7" href="#_subfunctions" class="code">function instances = extract(CSP,sMatrix)</a>
+0117             
+0118             [numTrials,numChannels,~] = size(sMatrix);
+0119             sMatrix = permute(sMatrix,[3,2,1]);
+0120             <span class="keyword">for</span> i=1:size(sMatrix,3);
+0121                 sMatrix(:,:,i) = (CSP.cspFilter*sMatrix(:,:,i)')';
+0122             <span class="keyword">end</span>
+0123             instances = zeros(numTrials,numChannels);
+0124             <span class="keyword">for</span> i=1:numTrials
+0125                 projectedTrial = sMatrix(:,:,i);
+0126                 variances = var(projectedTrial,0,1);
+0127                 instances(i,:) = log(variances)';
+0128             <span class="keyword">end</span>
+0129 <span class="comment">%             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);</span>
+0130         <span class="keyword">end</span>
+0131     <span class="keyword">end</span>
+0132 <span class="keyword">end</span>
+0133</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.m b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.m
new file mode 100644
index 0000000..e9765cc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.m
@@ -0,0 +1,133 @@
+classdef CSPWrapper < eegtoolkit.classification.ClassifierBase;
+    properties (Constant)
+        
+    end
+    properties
+        baseClassifier;
+        channel;
+        cspFilter;
+    end
+    
+    methods (Access = public)
+        function CSP = CSPWrapper(instanceSet)
+%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')
+%                 CSP.instanceSet = instanceSet;
+%             else
+%                 error('RawSignal extractor should be used with CSPWrapper');
+%             end
+        end
+        
+        
+        function CSP = build(CSP)
+            % Builds the classification models
+            CSP.learnCSPMatrix(CSP.instanceSet.sMatrix,CSP.instanceSet.labels);
+            instanceLocal = CSP.extract(CSP.instanceSet.sMatrix);
+            CSP.baseClassifier.instanceSet = eegtoolkit.util.InstanceSet(instanceLocal,CSP.instanceSet.labels);
+            CSP.baseClassifier.build;
+            CSP.reset;
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(CSP,instance)
+%             instance = CSP.extract
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            testInstances = CSP.extract(instance);
+            [output, probabilities, ranking] = CSP.baseClassifier.classifyInstance(testInstances);
+%             numModels = length(LSVM.models);
+%             [numinstance, ~] = size(testInstances);
+%             scores = zeros(numModels,numinstance);
+%             for i=1:numModels
+%                 %predict using the stored models
+%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = t(:,1);
+%             end
+%             output = zeros(numinstance,1);
+%             probabilities = zeros(numinstance,1);
+%             ranking = scores;
+%             for i=1:numinstance
+%                 %select the class with the highest probability
+%                 [prob, idx] = max(scores(:,i));
+%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+%                 %output the label with highest probability
+%                 output(i,1) = uniqueLabels(idx);
+%                 %return the probability for the output label
+%                 probabilities(i,1) = prob;
+%             end
+        end
+        
+        function CSP = reset(CSP)
+            % 'Resets' the classifier.
+%             CSP.models = {};
+        end
+        
+        function configInfo = getConfigInfo(CSP)
+            configInfo = '\n';
+        end
+        
+                        
+        function time = getTime(CSP)
+            time = 0;
+        end
+    end
+    methods (Access = private)
+        function [] = learnCSPMatrix(CSP, sMatrix, labels)
+            [numTrials,numChannels,~] = size(sMatrix);
+%             labels = CSP.instanceSet.getLabels;
+%             sMatrix = permute(sMatrix,[2,3,1]);
+%             sMatrix = permute(sMatrix,[2 1 3]);
+            sMatrix = permute(sMatrix,[3,2,1]);
+            for i=1:numChannels
+                for j=1:numTrials
+                    sMatrix(:,i,j) = (sMatrix(:,i,j) - mean(sMatrix(:,i,j)));
+                end
+            end
+            trialCov = zeros(numChannels,numChannels,numTrials);
+            for t=1:length(labels)
+                E = sMatrix(:,:,t)';
+                EE = E * E';
+                trialCov(:,:,t) = EE ./trace(EE);
+            end
+            %TODO: works only for 2 labels, [1,2]
+            for c=1:2
+                covMat{c} = mean(trialCov(:,:,labels == c),3);
+            end
+            [U, D] = eig(covMat{1},covMat{2},'qz');
+            eigenvalues = diag(D);
+            [~,ind] = sort(eigenvalues,'descend');
+            U = U(:,ind);
+            CSP.cspFilter = U';
+%             for i=1:size(sMatrix,3);
+%                 sMatrix(:,:,i) = (cspFilter*sMatrix(:,:,i)')';
+%             end
+%             instances = zeros(numTrials,numChannels);
+%             for i=1:numTrials
+%                 projectedTrial = sMatrix(:,:,i);
+%                 variances = var(projectedTrial,0,1);
+%                 instances(i,:) = log(variances)';
+%             end
+%             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+        
+        function instances = extract(CSP,sMatrix)
+            
+            [numTrials,numChannels,~] = size(sMatrix);
+            sMatrix = permute(sMatrix,[3,2,1]);
+            for i=1:size(sMatrix,3);
+                sMatrix(:,:,i) = (CSP.cspFilter*sMatrix(:,:,i)')';
+            end
+            instances = zeros(numTrials,numChannels);
+            for i=1:numTrials
+                projectedTrial = sMatrix(:,:,i);
+                variances = var(projectedTrial,0,1);
+                instances(i,:) = log(variances)';
+            end
+%             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/graph.dot b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.dot
new file mode 100644
index 0000000..e4db5e4
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  CSPWrapper -> CSPWrapper;
+
+  CSPWrapper [URL="CSPWrapper.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html
new file mode 100644
index 0000000..1365d5e
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@CSPWrapper">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@CSPWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="CSPWrapper.html" title="CSPWrapper" alt="" coords="158,29,155,22,144,15,127,10,105,7,81,5,57,7,36,10,19,15,8,22,4,29,8,37,19,43,36,49,57,52,81,53,105,52,127,49,144,43,155,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/graph.map b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.map
new file mode 100644
index 0000000..04ea233
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.map
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diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/index.html b/doc/+eegtoolkit/+classification/@CSPWrapper/index.html
new file mode 100644
index 0000000..5f93366
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@CSPWrapper</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@CSPWrapper">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@CSPWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
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+  <meta name="robots" content="index, follow">
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+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@CSPWrapper</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="CSPWrapper.html">CSPWrapper</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html
new file mode 100644
index 0000000..0a4685a
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html
@@ -0,0 +1,115 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ClassifierBase</title>
+  <meta name="keywords" content="ClassifierBase">
+  <meta name="description" content="Abstract class for classification. Implement the functions for any">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@ClassifierBase</a> &gt; ClassifierBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ClassifierBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>Abstract class for classification. Implement the functions for any</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Abstract class for classification. Implement the functions for any
+ classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+ 
+ Properties:
+ instanceSet: the training/test set in an InstanceSet structure
+ 
+ Functions:
+Implement this function to train the classification models. Each
+implementation should define the type of models that are to be trained by
+the build function.
+   obj = obj.build();
+Implement this function to apply the classification models to the provided
+instance, where instance is a matrix #instances x #features including the
+instances. The function should return the following three outputs; 1)
+output, the classified labels of the instances (#instances x 1), 2)
+probabilities, the probabilities for the output label (instances x 1) and
+3) ranking, a matrix #instances x #classes with the probabilities of each
+instance for each class (used for multiclass classification).
+   [output, probabilities, ranking] = obj.classifyInstance(instance);
+Implement this function to reset the classifier (e.g. delete the stored
+classification models
+   obj.reset();
+Info &amp; run time so that the experiments are easily documented. configInfo
+is a string with the configuration information and time is of type double.
+   configInfo = obj.getConfigInfo();
+   time = obj.getTime();</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ClassifierBase.html" class="code" title="">ClassifierBase</a>	Abstract class for classification. Implement the functions for any</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ClassifierBase.html" class="code" title="">ClassifierBase</a>	Abstract class for classification. Implement the functions for any</li></ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ClassifierBase.m">ClassifierBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Abstract class for classification. Implement the functions for any</span>
+0002 <span class="comment">% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)</span>
+0003 <span class="comment">%</span>
+0004 <span class="comment">% Properties:</span>
+0005 <span class="comment">% instanceSet: the training/test set in an InstanceSet structure</span>
+0006 <span class="comment">%</span>
+0007 <span class="comment">% Functions:</span>
+0008 <span class="comment">%Implement this function to train the classification models. Each</span>
+0009 <span class="comment">%implementation should define the type of models that are to be trained by</span>
+0010 <span class="comment">%the build function.</span>
+0011 <span class="comment">%   obj = obj.build();</span>
+0012 <span class="comment">%Implement this function to apply the classification models to the provided</span>
+0013 <span class="comment">%instance, where instance is a matrix #instances x #features including the</span>
+0014 <span class="comment">%instances. The function should return the following three outputs; 1)</span>
+0015 <span class="comment">%output, the classified labels of the instances (#instances x 1), 2)</span>
+0016 <span class="comment">%probabilities, the probabilities for the output label (instances x 1) and</span>
+0017 <span class="comment">%3) ranking, a matrix #instances x #classes with the probabilities of each</span>
+0018 <span class="comment">%instance for each class (used for multiclass classification).</span>
+0019 <span class="comment">%   [output, probabilities, ranking] = obj.classifyInstance(instance);</span>
+0020 <span class="comment">%Implement this function to reset the classifier (e.g. delete the stored</span>
+0021 <span class="comment">%classification models</span>
+0022 <span class="comment">%   obj.reset();</span>
+0023 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0024 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0025 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0026 <span class="comment">%   time = obj.getTime();</span>
+0027 
+0028 classdef (Abstract) <a href="ClassifierBase.html" class="code" title="">ClassifierBase</a> &lt; handle
+0029     
+0030     properties
+0031         instanceSet;
+0032     <span class="keyword">end</span>
+0033     
+0034     methods (Abstract = true)
+0035         [output, probabilities, ranking] = classifyInstance(obj,instance);
+0036         obj = build(obj);
+0037         obj = reset(obj);
+0038         configInfo = getConfigInfo(obj);
+0039         time = getTime(obj);
+0040     <span class="keyword">end</span>
+0041     
+0042 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
new file mode 100644
index 0000000..ad07e26
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
@@ -0,0 +1,42 @@
+% Abstract class for classification. Implement the functions for any
+% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+% 
+% Properties:
+% instanceSet: the training/test set in an InstanceSet structure
+% 
+% Functions:
+%Implement this function to train the classification models. Each
+%implementation should define the type of models that are to be trained by
+%the build function.
+%   obj = obj.build();
+%Implement this function to apply the classification models to the provided
+%instance, where instance is a matrix #instances x #features including the
+%instances. The function should return the following three outputs; 1)
+%output, the classified labels of the instances (#instances x 1), 2)
+%probabilities, the probabilities for the output label (instances x 1) and
+%3) ranking, a matrix #instances x #classes with the probabilities of each
+%instance for each class (used for multiclass classification).
+%   [output, probabilities, ranking] = obj.classifyInstance(instance);
+%Implement this function to reset the classifier (e.g. delete the stored
+%classification models
+%   obj.reset();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+classdef (Abstract) ClassifierBase < handle
+    
+    properties
+        instanceSet;
+    end
+    
+    methods (Abstract = true)
+        [output, probabilities, ranking] = classifyInstance(obj,instance);
+        obj = build(obj);
+        obj = reset(obj);
+        configInfo = getConfigInfo(obj);
+        time = getTime(obj);
+    end
+    
+end
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/graph.dot b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.dot
new file mode 100644
index 0000000..83eb9bc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ClassifierBase -> ClassifierBase;
+
+  ClassifierBase [URL="ClassifierBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html
new file mode 100644
index 0000000..225726d
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@ClassifierBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@ClassifierBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ClassifierBase.html" title="ClassifierBase" alt="" coords="169,29,165,22,153,15,135,10,112,7,87,5,61,7,38,10,20,15,8,22,4,29,8,37,20,43,38,49,61,52,87,53,112,52,135,49,153,43,165,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/graph.map b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.map
new file mode 100644
index 0000000..d23b2fe
--- /dev/null
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@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="ClassifierBase.html" title="ClassifierBase" alt="" coords="169,29,165,22,153,15,135,10,112,7,87,5,61,7,38,10,20,15,8,22,4,29,8,37,20,43,38,49,61,52,87,53,112,52,135,49,153,43,165,37">
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diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/index.html b/doc/+eegtoolkit/+classification/@ClassifierBase/index.html
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+
+<h1>Index for ./+eegtoolkit/+classification/@ClassifierBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ClassifierBase.html">ClassifierBase</a></td><td>Abstract class for classification. Implement the functions for any </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
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diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html b/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of CombiCCA</title>
+  <meta name="keywords" content="CombiCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@CombiCCA</a> &gt; CombiCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>CombiCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CombiCCA.html" class="code" title="">CombiCCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CombiCCA.html" class="code" title="">CombiCCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CoCCA = CombiCCA( sti_f, numHarmonics, sampleLength, samplingRate)</a></li><li><a href="#_sub2" class="code">function CoCCA = build(CoCCA)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(CoCCA,instance)</a></li><li><a href="#_sub4" class="code">function CSP = reset(CSP)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(CSP)</a></li><li><a href="#_sub6" class="code">function time = getTime(CSP)</a></li><li><a href="#_sub7" class="code">function [Wx, Wy, r] = cca(CCA,X,Y)</a></li><li><a href="#_sub8" class="code">function instancesOutput = extract(CoCCA,sMatrix)</a></li><li><a href="#_sub9" class="code">function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="CombiCCA.m">CombiCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="CombiCCA.html" class="code" title="">CombiCCA</a> &lt; eegtoolkit.classification.ClassifierBase;
+0002     <span class="comment">%COMBICCA Summary of this class goes here</span>
+0003     <span class="comment">%   Detailed explanation goes here</span>
+0004     <span class="comment">%     fprintf('CombitCCA Processing TW %fs, No.crossvalidation %d \n',TW(tw_length),run);</span>
+0005     <span class="comment">%                         it=cell(12,1);</span>
+0006     <span class="comment">%                         for iN = 1:nClasses</span>
+0007     <span class="comment">%                             it{iN} = mean(SSVEPdata(chan_used,1:TW_p(tw_length),idx_traindata,iN),3);</span>
+0008     <span class="comment">%                         end</span>
+0009     <span class="comment">%                         % recognize SSVEP</span>
+0010     properties
+0011         individualTemplates;
+0012         refSignals;
+0013         <span class="comment">%         sti_f;</span>
+0014         baseClassifier;
+0015     <span class="keyword">end</span>
+0016     
+0017     methods
+0018         <a name="_sub0" href="#_subfunctions" class="code">function CoCCA = CombiCCA( sti_f, numHarmonics, sampleLength, samplingRate)</a>
+0019             <span class="comment">%             CoCCA.sti_f = sti_f;</span>
+0020             <span class="comment">%             CoCCA.numHarmonics = numHarmonics;</span>
+0021             CoCCA.refSignals = CoCCA.ck_signalTrans(sti_f,sampleLength, samplingRate, numHarmonics);
+0022         <span class="keyword">end</span>
+0023         
+0024         <a name="_sub1" href="#_subfunctions" class="code">function CoCCA = build(CoCCA)</a>
+0025             numLabels = length(unique(CoCCA.instanceSet.labels));
+0026             CoCCA.individualTemplates = cell(numLabels,1);
+0027             unLabels = unique(CoCCA.instanceSet.labels);
+0028             <span class="keyword">for</span> i=1:numLabels
+0029                 trialsIndices = CoCCA.instanceSet.labels==unLabels(i);
+0030                 CoCCA.individualTemplates{i} = squeeze(mean(CoCCA.instanceSet.sMatrix(trialsIndices,:,:),1));
+0031             <span class="keyword">end</span>
+0032             
+0033         <span class="keyword">end</span>
+0034         
+0035         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(CoCCA,instance)</a>
+0036             testInstances = CoCCA.extract(instance);
+0037             [output, probabilities, ranking] = CoCCA.baseClassifier.classifyInstance(testInstances);
+0038         <span class="keyword">end</span>
+0039         
+0040         <a name="_sub3" href="#_subfunctions" class="code">function CSP = reset(CSP)</a>
+0041             <span class="comment">% 'Resets' the classifier.</span>
+0042             <span class="comment">%             CSP.models = {};</span>
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CSP)</a>
+0046             configInfo = <span class="string">'\n'</span>;
+0047         <span class="keyword">end</span>
+0048         
+0049         
+0050         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(CSP)</a>
+0051             time = 0;
+0052         <span class="keyword">end</span>
+0053         
+0054     <span class="keyword">end</span>
+0055     methods (Access = private)
+0056         
+0057         <a name="_sub6" href="#_subfunctions" class="code">function [Wx, Wy, r] = cca(CCA,X,Y)</a>
+0058             <span class="comment">%</span>
+0059             <span class="comment">% CCA calculate canonical correlations</span>
+0060             <span class="comment">%</span>
+0061             <span class="comment">% [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation</span>
+0062             
+0063             <span class="comment">% vectors as columns and r is a vector with corresponding canonical</span>
+0064             <span class="comment">% correlations. The correlations are sorted in descending order. X and Y</span>
+0065             <span class="comment">% are matrices where each column is a sample. Hence, X and Y must have</span>
+0066             <span class="comment">% the same number of columns.</span>
+0067             <span class="comment">%</span>
+0068             <span class="comment">% Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is</span>
+0069             <span class="comment">% then M*L, Wy is N*L and r is L*1.</span>
+0070             <span class="comment">%</span>
+0071             <span class="comment">%</span>
+0072             <span class="comment">% ?? 2000 Magnus Borga, Link?pings universitet</span>
+0073             
+0074             <span class="comment">% --- Calculate covariance matrices ---??????????????</span>
+0075             
+0076             z = [X;Y];
+0077             C = cov(z.');
+0078             sx = size(X,1);   <span class="comment">%X??????(??),</span>
+0079             sy = size(Y,1);
+0080             Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+0081             Cxy = C(1:sx, sx+1:sx+sy);
+0082             Cyx = Cxy';
+0083             Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);<span class="comment">%eye()????????</span>
+0084             invCyy = inv(Cyy);
+0085             
+0086             <span class="comment">% --- Calcualte Wx and r ---</span>
+0087             
+0088             [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); <span class="comment">% Basis in X eig????????????</span>
+0089             r = sqrt(real(r));      <span class="comment">% Canonical correlations</span>
+0090             
+0091             <span class="comment">% --- Sort correlations ---</span>
+0092             
+0093             V = fliplr(Wx);        <span class="comment">% reverse order of eigenvectors??????????????????????i??????????i??????</span>
+0094             r = flipud(diag(r));    <span class="comment">% extract eigenvalues and reverse their order</span>
+0095             [r,I]= sort((real(r)));    <span class="comment">% sort reversed eigenvalues in ascending order</span>
+0096             r = flipud(r);        <span class="comment">% restore sorted eigenvalues into descending order??????????????</span>
+0097             <span class="keyword">for</span> j = 1:length(I)
+0098                 Wx(:,j) = V(:,I(j));  <span class="comment">% sort reversed eigenvectors in ascending order</span>
+0099             <span class="keyword">end</span>
+0100             Wx = fliplr(Wx);    <span class="comment">% restore sorted eigenvectors into descending order</span>
+0101             
+0102             <span class="comment">% --- Calcualte Wy  ---</span>
+0103             
+0104             Wy = invCyy*Cyx*Wx;     <span class="comment">% Basis in Y</span>
+0105             <span class="comment">% Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy</span>
+0106             
+0107         <span class="keyword">end</span>
+0108         <a name="_sub7" href="#_subfunctions" class="code">function instancesOutput = extract(CoCCA,sMatrix)</a>
+0109             numClasses = length(CoCCA.individualTemplates);
+0110             numInstances = size(sMatrix,1);
+0111             instancesOutput = zeros(numInstances,numClasses);
+0112             <span class="keyword">for</span> i=1:numInstances
+0113                 <span class="keyword">for</span> j=1:numClasses
+0114                     [wxit,wyit,rit] = CoCCA.cca(squeeze(sMatrix(i,:,:)),CoCCA.individualTemplates{j});
+0115                     [wxref,wyref,rref] = CoCCA.cca(squeeze(sMatrix(i,:,:)),CoCCA.refSignals(:,:,j));
+0116                     [wxitref,wyitref,ritref] = CoCCA.cca(CoCCA.individualTemplates{j},CoCCA.refSignals(:,:,j));
+0117                     q1 = squeeze(sMatrix(i,:,:))'*wxref;
+0118                     q2 = CoCCA.refSignals(:,:,j)'*wyref;
+0119                     q3 = squeeze(sMatrix(i,:,:))'*wxit;
+0120                     q4 = CoCCA.individualTemplates{j}'*wxit;
+0121                     q5 = q1;
+0122                     q6 = CoCCA.individualTemplates{j}'*wxref;
+0123                     q7 = squeeze(sMatrix(i,:,:))'*wxitref;
+0124                     q8 = CoCCA.individualTemplates{j}'*wxitref;
+0125                     r_n = [corr(q1(:),q2(:)) corr(q3(:),q4(:)) corr(q5(:),q6(:)) corr(q7(:), q8(:))];
+0126                     rho_n = sum(sign(r_n).*r_n.^2);
+0127                     instancesOutput(i,j) = rho_n;
+0128                 <span class="keyword">end</span>
+0129             <span class="keyword">end</span>
+0130         <span class="keyword">end</span>
+0131         <span class="comment">%                         for j=1:nClasses</span>
+0132         <span class="comment">%                             tempvec=zeros(nClasses,1);</span>
+0133         <span class="comment">%                             for jj=1:nClasses</span>
+0134         <span class="comment">%                                 [wxit,wyit,rit ]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));</span>
+0135         <span class="comment">%                                 [wxref,wyref,rref ]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),sc{jj}(:,1:TW_p(tw_length)));</span>
+0136         <span class="comment">%                                 [wxitref,wyitref,ritref ]=cca(it{jj}(:,1:TW_p(tw_length)),sc{jj}(:,1:TW_p(tw_length)));</span>
+0137         <span class="comment">%                                 q1 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxref;</span>
+0138         <span class="comment">%                                 q2 = sc{jj}(:,1:TW_p(tw_length))'*wyref;</span>
+0139         <span class="comment">%                                 q3 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxit;</span>
+0140         <span class="comment">%                                 q4 = it{jj}(:,1:TW_p(tw_length))'*wxit;</span>
+0141         <span class="comment">%                                 q5 = q1;</span>
+0142         <span class="comment">%                                 q6 = it{jj}(:,1:TW_p(tw_length))'*wxref;</span>
+0143         <span class="comment">%                                 q7 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxitref;</span>
+0144         <span class="comment">%                                 q8 = it{jj}(:,1:TW_p(tw_length))'*wxitref;</span>
+0145         <span class="comment">%                                 r_n = [corr(q1(:),q2(:)) corr(q3(:),q4(:)) corr(q5(:),q6(:)) corr(q7(:),q8(:))];</span>
+0146         <span class="comment">%                                 rho_n = sum(sign(r_n).*r_n.^2);</span>
+0147         <span class="comment">%                                 tempvec(jj) = rho_n;%max(r1);</span>
+0148         <span class="comment">%                             end</span>
+0149         <span class="comment">%</span>
+0150         <span class="comment">%                             [v,idx]=max(tempvec);</span>
+0151         <span class="comment">%                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;</span>
+0152         <span class="comment">%                             if idx==j</span>
+0153         <span class="comment">%                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;</span>
+0154         <span class="comment">%                             end</span>
+0155         <span class="comment">%                         end</span>
+0156         <a name="_sub8" href="#_subfunctions" class="code">function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)</a>
+0157             
+0158             p=mLen;<span class="comment">%1250;</span>
+0159             fs=FreqSamp;<span class="comment">%250;</span>
+0160             TP=1/fs:1/fs:p/fs;
+0161             <span class="keyword">for</span> j=1:length(f)
+0162                 tempComp=[];
+0163                 <span class="keyword">for</span> k=1:NumHarm
+0164                     Sinh1=sin(2*pi*k*f(j)*TP);
+0165                     Cosh1=cos(2*pi*k*f(j)*TP);
+0166                     tempComp = [tempComp; Sinh1;Cosh1;];
+0167                 <span class="keyword">end</span>
+0168                 refSignal(:,:,j)=tempComp;
+0169             <span class="keyword">end</span>
+0170         <span class="keyword">end</span>
+0171     <span class="keyword">end</span>
+0172 <span class="keyword">end</span>
+0173</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.m b/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.m
new file mode 100644
index 0000000..585d5a0
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.m
@@ -0,0 +1,173 @@
+classdef CombiCCA < eegtoolkit.classification.ClassifierBase;
+    %COMBICCA Summary of this class goes here
+    %   Detailed explanation goes here
+    %     fprintf('CombitCCA Processing TW %fs, No.crossvalidation %d \n',TW(tw_length),run);
+    %                         it=cell(12,1);
+    %                         for iN = 1:nClasses
+    %                             it{iN} = mean(SSVEPdata(chan_used,1:TW_p(tw_length),idx_traindata,iN),3);
+    %                         end
+    %                         % recognize SSVEP
+    properties
+        individualTemplates;
+        refSignals;
+        %         sti_f;
+        baseClassifier;
+    end
+    
+    methods
+        function CoCCA = CombiCCA( sti_f, numHarmonics, sampleLength, samplingRate)
+            %             CoCCA.sti_f = sti_f;
+            %             CoCCA.numHarmonics = numHarmonics;
+            CoCCA.refSignals = CoCCA.ck_signalTrans(sti_f,sampleLength, samplingRate, numHarmonics);
+        end
+        
+        function CoCCA = build(CoCCA)
+            numLabels = length(unique(CoCCA.instanceSet.labels));
+            CoCCA.individualTemplates = cell(numLabels,1);
+            unLabels = unique(CoCCA.instanceSet.labels);
+            for i=1:numLabels
+                trialsIndices = CoCCA.instanceSet.labels==unLabels(i);
+                CoCCA.individualTemplates{i} = squeeze(mean(CoCCA.instanceSet.sMatrix(trialsIndices,:,:),1));
+            end
+            
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(CoCCA,instance)
+            testInstances = CoCCA.extract(instance);
+            [output, probabilities, ranking] = CoCCA.baseClassifier.classifyInstance(testInstances);
+        end
+        
+        function CSP = reset(CSP)
+            % 'Resets' the classifier.
+            %             CSP.models = {};
+        end
+        
+        function configInfo = getConfigInfo(CSP)
+            configInfo = '\n';
+        end
+        
+        
+        function time = getTime(CSP)
+            time = 0;
+        end
+        
+    end
+    methods (Access = private)
+        
+        function [Wx, Wy, r] = cca(CCA,X,Y)
+            %
+            % CCA calculate canonical correlations
+            %
+            % [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation
+            
+            % vectors as columns and r is a vector with corresponding canonical
+            % correlations. The correlations are sorted in descending order. X and Y
+            % are matrices where each column is a sample. Hence, X and Y must have
+            % the same number of columns.
+            %
+            % Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is
+            % then M*L, Wy is N*L and r is L*1.
+            %
+            %
+            % ?? 2000 Magnus Borga, Link?pings universitet
+            
+            % --- Calculate covariance matrices ---??????????????
+            
+            z = [X;Y];
+            C = cov(z.');
+            sx = size(X,1);   %X??????(??),
+            sy = size(Y,1);
+            Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+            Cxy = C(1:sx, sx+1:sx+sy);
+            Cyx = Cxy';
+            Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);%eye()????????
+            invCyy = inv(Cyy);
+            
+            % --- Calcualte Wx and r ---
+            
+            [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); % Basis in X eig????????????
+            r = sqrt(real(r));      % Canonical correlations
+            
+            % --- Sort correlations ---
+            
+            V = fliplr(Wx);		% reverse order of eigenvectors??????????????????????i??????????i??????
+            r = flipud(diag(r));	% extract eigenvalues and reverse their order
+            [r,I]= sort((real(r)));	% sort reversed eigenvalues in ascending order
+            r = flipud(r);		% restore sorted eigenvalues into descending order??????????????
+            for j = 1:length(I)
+                Wx(:,j) = V(:,I(j));  % sort reversed eigenvectors in ascending order
+            end
+            Wx = fliplr(Wx);	% restore sorted eigenvectors into descending order
+            
+            % --- Calcualte Wy  ---
+            
+            Wy = invCyy*Cyx*Wx;     % Basis in Y
+            % Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy
+            
+        end
+        function instancesOutput = extract(CoCCA,sMatrix)
+            numClasses = length(CoCCA.individualTemplates);
+            numInstances = size(sMatrix,1);
+            instancesOutput = zeros(numInstances,numClasses);
+            for i=1:numInstances
+                for j=1:numClasses
+                    [wxit,wyit,rit] = CoCCA.cca(squeeze(sMatrix(i,:,:)),CoCCA.individualTemplates{j});
+                    [wxref,wyref,rref] = CoCCA.cca(squeeze(sMatrix(i,:,:)),CoCCA.refSignals(:,:,j));
+                    [wxitref,wyitref,ritref] = CoCCA.cca(CoCCA.individualTemplates{j},CoCCA.refSignals(:,:,j));
+                    q1 = squeeze(sMatrix(i,:,:))'*wxref;
+                    q2 = CoCCA.refSignals(:,:,j)'*wyref;
+                    q3 = squeeze(sMatrix(i,:,:))'*wxit;
+                    q4 = CoCCA.individualTemplates{j}'*wxit;
+                    q5 = q1;
+                    q6 = CoCCA.individualTemplates{j}'*wxref;
+                    q7 = squeeze(sMatrix(i,:,:))'*wxitref;
+                    q8 = CoCCA.individualTemplates{j}'*wxitref;
+                    r_n = [corr(q1(:),q2(:)) corr(q3(:),q4(:)) corr(q5(:),q6(:)) corr(q7(:), q8(:))];
+                    rho_n = sum(sign(r_n).*r_n.^2);
+                    instancesOutput(i,j) = rho_n;
+                end
+            end
+        end
+        %                         for j=1:nClasses
+        %                             tempvec=zeros(nClasses,1);
+        %                             for jj=1:nClasses
+        %                                 [wxit,wyit,rit ]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));
+        %                                 [wxref,wyref,rref ]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),sc{jj}(:,1:TW_p(tw_length)));
+        %                                 [wxitref,wyitref,ritref ]=cca(it{jj}(:,1:TW_p(tw_length)),sc{jj}(:,1:TW_p(tw_length)));
+        %                                 q1 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxref;
+        %                                 q2 = sc{jj}(:,1:TW_p(tw_length))'*wyref;
+        %                                 q3 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxit;
+        %                                 q4 = it{jj}(:,1:TW_p(tw_length))'*wxit;
+        %                                 q5 = q1;
+        %                                 q6 = it{jj}(:,1:TW_p(tw_length))'*wxref;
+        %                                 q7 = SSVEPdata(chan_used,1:TW_p(tw_length),run,j)'*wxitref;
+        %                                 q8 = it{jj}(:,1:TW_p(tw_length))'*wxitref;
+        %                                 r_n = [corr(q1(:),q2(:)) corr(q3(:),q4(:)) corr(q5(:),q6(:)) corr(q7(:),q8(:))];
+        %                                 rho_n = sum(sign(r_n).*r_n.^2);
+        %                                 tempvec(jj) = rho_n;%max(r1);
+        %                             end
+        %
+        %                             [v,idx]=max(tempvec);
+        %                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;
+        %                             if idx==j
+        %                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;
+        %                             end
+        %                         end
+        function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)
+            
+            p=mLen;%1250;
+            fs=FreqSamp;%250;
+            TP=1/fs:1/fs:p/fs;
+            for j=1:length(f)
+                tempComp=[];
+                for k=1:NumHarm
+                    Sinh1=sin(2*pi*k*f(j)*TP);
+                    Cosh1=cos(2*pi*k*f(j)*TP);
+                    tempComp = [tempComp; Sinh1;Cosh1;];
+                end
+                refSignal(:,:,j)=tempComp;
+            end
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/graph.dot b/doc/+eegtoolkit/+classification/@CombiCCA/graph.dot
new file mode 100644
index 0000000..9da7469
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  CombiCCA -> CombiCCA;
+
+  CombiCCA [URL="CombiCCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/graph.html b/doc/+eegtoolkit/+classification/@CombiCCA/graph.html
new file mode 100644
index 0000000..aa35708
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@CombiCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@CombiCCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@CombiCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@CombiCCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@CombiCCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="CombiCCA.html" title="CombiCCA" alt="" coords="147,29,144,22,133,15,118,10,98,7,76,5,54,7,34,10,19,15,8,22,5,29,8,37,19,43,34,49,54,52,76,53,98,52,118,49,133,43,144,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/graph.map b/doc/+eegtoolkit/+classification/@CombiCCA/graph.map
new file mode 100644
index 0000000..4f27966
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="CombiCCA.html" title="CombiCCA" alt="" coords="147,29,144,22,133,15,118,10,98,7,76,5,54,7,34,10,19,15,8,22,5,29,8,37,19,43,34,49,54,52,76,53,98,52,118,49,133,43,144,37">
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diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/index.html b/doc/+eegtoolkit/+classification/@CombiCCA/index.html
new file mode 100644
index 0000000..3208d55
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@CombiCCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@CombiCCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@CombiCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@CombiCCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="CombiCCA.html">CombiCCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html
new file mode 100644
index 0000000..3bc50b3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html
@@ -0,0 +1,121 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FusionClassifierWrapper</title>
+  <meta name="keywords" content="FusionClassifierWrapper">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@FusionClassifierWrapper</a> &gt; FusionClassifierWrapper.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FusionClassifierWrapper
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FusionClassifierWrapper.html" class="code" title="">FusionClassifierWrapper</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FusionClassifierWrapper.html" class="code" title="">FusionClassifierWrapper</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function FCW = FusionClassifierWrapper(baseClassifier, fusionInstanceSet)</a></li><li><a href="#_sub2" class="code">function FCW = build(FCW)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking]  = classifyInstance(FCW,instance)</a></li><li><a href="#_sub4" class="code">function configInfo = getConfigInfo(FCW)</a></li><li><a href="#_sub5" class="code">function time = getTime(FCW)</a></li><li><a href="#_sub6" class="code">function FCW = reset(FCW)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FusionClassifierWrapper.m">FusionClassifierWrapper.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="FusionClassifierWrapper.html" class="code" title="">FusionClassifierWrapper</a> &lt; eegtoolkit.classification.ClassifierBase &amp; eegtoolkit.experiment.Experimenter;
+0002     
+0003     properties
+0004         baseClassifier;
+0005         classifiers;
+0006     <span class="keyword">end</span>
+0007     
+0008     methods
+0009         <a name="_sub0" href="#_subfunctions" class="code">function FCW = FusionClassifierWrapper(baseClassifier, fusionInstanceSet)</a>
+0010             <span class="keyword">if</span> nargin&gt;0
+0011                 FCW.baseClassifier = baseClassifier;
+0012             <span class="keyword">end</span>
+0013             <span class="keyword">if</span> nargin&gt;1
+0014                 FCW.instanceSet = fusionInstanceSet;
+0015             <span class="keyword">end</span>
+0016         <span class="keyword">end</span>
+0017         
+0018         <a name="_sub1" href="#_subfunctions" class="code">function FCW = build(FCW)</a>
+0019             numFusion = FCW.instanceSet.numFusion;
+0020             FCW.reset;
+0021             <span class="keyword">if</span> ~isa(FCW.baseClassifier,<span class="string">'eegtoolkit.classification.LIBSVM'</span>)
+0022                 error (<span class="string">'Only LIBSVMClassifier supported as base classifier'</span>);
+0023             <span class="keyword">else</span>
+0024                 <span class="keyword">for</span> i=1:numFusion
+0025                     FCW.classifiers{i} = FCW.baseClassifier.copy;
+0026                     FCW.classifiers{i} = eegtoolkit.classification.LIBSVM;
+0027                     FCW.classifiers{i}.instanceSet = FCW.instanceSet.instanceSets{i};
+0028                     FCW.classifiers{i}.build;
+0029                 <span class="keyword">end</span>
+0030             <span class="keyword">end</span>
+0031         <span class="keyword">end</span>
+0032         
+0033         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking]  = classifyInstance(FCW,instance)</a>
+0034             [numInstances,~] = size(instance);
+0035             numClass = length(FCW.classifiers);
+0036             out = zeros(numInstances,numClass);
+0037             output = zeros(numInstances,1);
+0038             <span class="keyword">for</span> i=1:length(FCW.classifiers)
+0039                 [out(:,i), probabilities, ranking] = FCW.classifiers{i}.classifyInstance(instance(:,:,i));
+0040             <span class="keyword">end</span>
+0041             <span class="keyword">for</span> i=1:numInstances
+0042                 x = out(i,:);
+0043                 [a,b] = hist(x,unique(x));
+0044                 [~,idx] = max(a);
+0045                 output(i,:) = b(idx);
+0046             <span class="keyword">end</span>
+0047             probabilities = [];
+0048             ranking = [];
+0049             <span class="comment">%TODO:*****</span>
+0050             
+0051         <span class="keyword">end</span>
+0052         
+0053         <a name="_sub3" href="#_subfunctions" class="code">function configInfo = getConfigInfo(FCW)</a>
+0054             configInfo = <span class="string">'FusionClassifierWrapper'</span>;
+0055         <span class="keyword">end</span>
+0056         
+0057                         
+0058         <a name="_sub4" href="#_subfunctions" class="code">function time = getTime(FCW)</a>
+0059             time = 0;
+0060         <span class="keyword">end</span>
+0061         
+0062         <a name="_sub5" href="#_subfunctions" class="code">function FCW = reset(FCW)</a>
+0063             FCW.classifiers = {};
+0064         <span class="keyword">end</span>
+0065         
+0066         
+0067         
+0068     <span class="keyword">end</span>
+0069     
+0070 <span class="keyword">end</span>
+0071</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.m b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.m
new file mode 100644
index 0000000..6da94ff
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.m
@@ -0,0 +1,71 @@
+classdef FusionClassifierWrapper < eegtoolkit.classification.ClassifierBase & eegtoolkit.experiment.Experimenter;
+    
+    properties
+        baseClassifier;
+        classifiers;
+    end
+    
+    methods
+        function FCW = FusionClassifierWrapper(baseClassifier, fusionInstanceSet)
+            if nargin>0
+                FCW.baseClassifier = baseClassifier;
+            end
+            if nargin>1
+                FCW.instanceSet = fusionInstanceSet;
+            end
+        end
+        
+        function FCW = build(FCW)
+            numFusion = FCW.instanceSet.numFusion;
+            FCW.reset;
+            if ~isa(FCW.baseClassifier,'eegtoolkit.classification.LIBSVM')
+                error ('Only LIBSVMClassifier supported as base classifier');
+            else
+                for i=1:numFusion
+                    FCW.classifiers{i} = FCW.baseClassifier.copy;
+                    FCW.classifiers{i} = eegtoolkit.classification.LIBSVM;
+                    FCW.classifiers{i}.instanceSet = FCW.instanceSet.instanceSets{i};
+                    FCW.classifiers{i}.build;
+                end
+            end
+        end
+        
+        function [output, probabilities, ranking]  = classifyInstance(FCW,instance)
+            [numInstances,~] = size(instance);
+            numClass = length(FCW.classifiers);
+            out = zeros(numInstances,numClass);
+            output = zeros(numInstances,1);
+            for i=1:length(FCW.classifiers)
+                [out(:,i), probabilities, ranking] = FCW.classifiers{i}.classifyInstance(instance(:,:,i));
+            end
+            for i=1:numInstances
+                x = out(i,:);
+                [a,b] = hist(x,unique(x));
+                [~,idx] = max(a);
+                output(i,:) = b(idx);
+            end
+            probabilities = [];
+            ranking = [];
+            %TODO:*****
+            
+        end
+        
+        function configInfo = getConfigInfo(FCW)
+            configInfo = 'FusionClassifierWrapper';
+        end
+        
+                        
+        function time = getTime(FCW)
+            time = 0;
+        end
+        
+        function FCW = reset(FCW)
+            FCW.classifiers = {};
+        end
+        
+        
+        
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.dot b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.dot
new file mode 100644
index 0000000..14ffcbc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FusionClassifierWrapper -> FusionClassifierWrapper;
+
+  FusionClassifierWrapper [URL="FusionClassifierWrapper.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html
new file mode 100644
index 0000000..4d5449b
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FusionClassifierWrapper.html" title="FusionClassifierWrapper" alt="" coords="270,29,263,22,245,15,215,10,178,7,137,5,96,7,59,10,30,15,11,22,5,29,11,37,30,43,59,49,96,52,137,53,178,52,215,49,245,43,263,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.map b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html
new file mode 100644
index 0000000..0491c84
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@FusionClassifierWrapper</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FusionClassifierWrapper.html">FusionClassifierWrapper</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html
new file mode 100644
index 0000000..4d13209
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html
@@ -0,0 +1,256 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ITCCA</title>
+  <meta name="keywords" content="ITCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@ITCCA</a> &gt; ITCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ITCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ITCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ITCCA.html" class="code" title="">ITCCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ITCCA.html" class="code" title="">ITCCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function IT = ITCCA(instanceSet)</a></li><li><a href="#_sub2" class="code">function IT = build(IT)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(CSP,instance)</a></li><li><a href="#_sub4" class="code">function CSP = reset(CSP)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(CSP)</a></li><li><a href="#_sub6" class="code">function time = getTime(CSP)</a></li><li><a href="#_sub7" class="code">function [Wx, Wy, r] = cca(CCA,X,Y)</a></li><li><a href="#_sub8" class="code">function instancesOutput = extract(IT,sMatrix)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ITCCA.m">ITCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="ITCCA.html" class="code" title="">ITCCA</a> &lt; eegtoolkit.classification.ClassifierBase;
+0002     <span class="comment">%                 instanceStruct = struct('sMatrix',sMatrix, 'labels', labels);</span>
+0003     <span class="comment">%     it=cell(12,1);</span>
+0004     <span class="comment">%                         for iN = 1:nClasses</span>
+0005     <span class="comment">%                             it{iN} = mean(SSVEPdata(chan_used,1:TW_p(tw_length),idx_traindata,iN),3);</span>
+0006     <span class="comment">%                         end</span>
+0007     <span class="comment">%                         % recognize SSVEP</span>
+0008     <span class="comment">%                         for j=1:nClasses</span>
+0009     <span class="comment">%                             tempvec=zeros(nClasses,1);</span>
+0010     <span class="comment">%                             for jj=1:nClasses</span>
+0011     <span class="comment">%                                 [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));</span>
+0012     <span class="comment">%                                 tempvec(jj) = max(r1);</span>
+0013     <span class="comment">%                             end</span>
+0014     <span class="comment">%</span>
+0015     <span class="comment">%                             [v,idx]=max(tempvec);</span>
+0016     <span class="comment">%                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;</span>
+0017     <span class="comment">%                             if idx==j</span>
+0018     <span class="comment">%                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;</span>
+0019     <span class="comment">%                             end</span>
+0020     <span class="comment">%                         end</span>
+0021     properties (Constant)
+0022         
+0023     <span class="keyword">end</span>
+0024     properties
+0025         baseClassifier;
+0026         individualTemplates;
+0027     <span class="keyword">end</span>
+0028     
+0029     methods (Access = public)
+0030         <a name="_sub0" href="#_subfunctions" class="code">function IT = ITCCA(instanceSet)</a>
+0031             <span class="comment">%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')</span>
+0032             <span class="comment">%                 CSP.instanceSet = instanceSet;</span>
+0033             <span class="comment">%             else</span>
+0034             <span class="comment">%                 error('RawSignal extractor should be used with CSPWrapper');</span>
+0035             <span class="comment">%             end</span>
+0036         <span class="keyword">end</span>
+0037         
+0038         
+0039         <a name="_sub1" href="#_subfunctions" class="code">function IT = build(IT)</a>
+0040             <span class="comment">% Builds the classification models</span>
+0041             <span class="comment">%             IT.learnCSPMatrix(IT.instanceSet.sMatrix,IT.instanceSet.labels);</span>
+0042             numLabels = length(unique(IT.instanceSet.labels));
+0043             IT.individualTemplates = cell(numLabels,1);
+0044             unLabels = unique(IT.instanceSet.labels);
+0045             <span class="keyword">for</span> i = 1:numLabels
+0046                 trialsIndices = IT.instanceSet.labels==unLabels(i);
+0047                 IT.individualTemplates{i} = squeeze(mean(IT.instanceSet.sMatrix(trialsIndices,:,:),1));
+0048             <span class="keyword">end</span>
+0049             <span class="comment">%             instances = IT.extract(IT.instanceSet.sMatrix);</span>
+0050             <span class="comment">%             instanceSet = eegtoolkit.util.InstanceSet(instances,IT.instanceSet.labels);</span>
+0051             <span class="comment">%             IT.baseClassifier.instanceSet = instanceSet;</span>
+0052             <span class="comment">%             IT.baseClassifier.build();</span>
+0053         <span class="keyword">end</span>
+0054         
+0055         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(CSP,instance)</a>
+0056             <span class="comment">%                         for j=1:nClasses</span>
+0057             <span class="comment">%                             tempvec=zeros(nClasses,1);</span>
+0058             <span class="comment">%                             for jj=1:nClasses</span>
+0059             <span class="comment">%                                 [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));</span>
+0060             <span class="comment">%                                 tempvec(jj) = max(r1);</span>
+0061             <span class="comment">%                             end</span>
+0062             <span class="comment">%</span>
+0063             <span class="comment">%                             [v,idx]=max(tempvec);</span>
+0064             <span class="comment">%                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;</span>
+0065             <span class="comment">%                             if idx==j</span>
+0066             <span class="comment">%                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;</span>
+0067             <span class="comment">%                             end</span>
+0068             <span class="comment">%                         end</span>
+0069             <span class="comment">%             instance = CSP.extract</span>
+0070             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0071             <span class="comment">%output = predicted class</span>
+0072             <span class="comment">%probabilities = probability for predicted class</span>
+0073             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0074             
+0075             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0076             testInstances = CSP.extract(instance);
+0077             [output, probabilities, ranking] = CSP.baseClassifier.classifyInstance(testInstances);
+0078             <span class="comment">%             numModels = length(LSVM.models);</span>
+0079             <span class="comment">%             [numinstance, ~] = size(testInstances);</span>
+0080             <span class="comment">%             scores = zeros(numModels,numinstance);</span>
+0081             <span class="comment">%             for i=1:numModels</span>
+0082             <span class="comment">%                 %predict using the stored models</span>
+0083             <span class="comment">%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');</span>
+0084             <span class="comment">%                 %store probability for each class</span>
+0085             <span class="comment">%                 scores(i,:) = t(:,1);</span>
+0086             <span class="comment">%             end</span>
+0087             <span class="comment">%             output = zeros(numinstance,1);</span>
+0088             <span class="comment">%             probabilities = zeros(numinstance,1);</span>
+0089             <span class="comment">%             ranking = scores;</span>
+0090             <span class="comment">%             for i=1:numinstance</span>
+0091             <span class="comment">%                 %select the class with the highest probability</span>
+0092             <span class="comment">%                 [prob, idx] = max(scores(:,i));</span>
+0093             <span class="comment">%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);</span>
+0094             <span class="comment">%                 %output the label with highest probability</span>
+0095             <span class="comment">%                 output(i,1) = uniqueLabels(idx);</span>
+0096             <span class="comment">%                 %return the probability for the output label</span>
+0097             <span class="comment">%                 probabilities(i,1) = prob;</span>
+0098             <span class="comment">%             end</span>
+0099         <span class="keyword">end</span>
+0100         
+0101         <a name="_sub3" href="#_subfunctions" class="code">function CSP = reset(CSP)</a>
+0102             <span class="comment">% 'Resets' the classifier.</span>
+0103             <span class="comment">%             CSP.models = {};</span>
+0104         <span class="keyword">end</span>
+0105         
+0106         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CSP)</a>
+0107             configInfo = <span class="string">'\n'</span>;
+0108         <span class="keyword">end</span>
+0109         
+0110         
+0111         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(CSP)</a>
+0112             time = 0;
+0113         <span class="keyword">end</span>
+0114     <span class="keyword">end</span>
+0115     
+0116     
+0117     methods (Access = private)
+0118         <a name="_sub6" href="#_subfunctions" class="code">function [Wx, Wy, r] = cca(CCA,X,Y)</a>
+0119             <span class="comment">%</span>
+0120             <span class="comment">% CCA calculate canonical correlations</span>
+0121             <span class="comment">%</span>
+0122             <span class="comment">% [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation</span>
+0123             
+0124             <span class="comment">% vectors as columns and r is a vector with corresponding canonical</span>
+0125             <span class="comment">% correlations. The correlations are sorted in descending order. X and Y</span>
+0126             <span class="comment">% are matrices where each column is a sample. Hence, X and Y must have</span>
+0127             <span class="comment">% the same number of columns.</span>
+0128             <span class="comment">%</span>
+0129             <span class="comment">% Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is</span>
+0130             <span class="comment">% then M*L, Wy is N*L and r is L*1.</span>
+0131             <span class="comment">%</span>
+0132             <span class="comment">%</span>
+0133             <span class="comment">% ?? 2000 Magnus Borga, Link?pings universitet</span>
+0134             
+0135             <span class="comment">% --- Calculate covariance matrices ---??????????????</span>
+0136             
+0137             z = [X;Y];
+0138             C = cov(z.');
+0139             sx = size(X,1);   <span class="comment">%X??????(??),</span>
+0140             sy = size(Y,1);
+0141             Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+0142             Cxy = C(1:sx, sx+1:sx+sy);
+0143             Cyx = Cxy';
+0144             Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);<span class="comment">%eye()????????</span>
+0145             invCyy = inv(Cyy);
+0146             
+0147             <span class="comment">% --- Calcualte Wx and r ---</span>
+0148             
+0149             [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); <span class="comment">% Basis in X eig????????????</span>
+0150             r = sqrt(real(r));      <span class="comment">% Canonical correlations</span>
+0151             
+0152             <span class="comment">% --- Sort correlations ---</span>
+0153             
+0154             V = fliplr(Wx);        <span class="comment">% reverse order of eigenvectors??????????????????????i??????????i??????</span>
+0155             r = flipud(diag(r));    <span class="comment">% extract eigenvalues and reverse their order</span>
+0156             [r,I]= sort((real(r)));    <span class="comment">% sort reversed eigenvalues in ascending order</span>
+0157             r = flipud(r);        <span class="comment">% restore sorted eigenvalues into descending order??????????????</span>
+0158             <span class="keyword">for</span> j = 1:length(I)
+0159                 Wx(:,j) = V(:,I(j));  <span class="comment">% sort reversed eigenvectors in ascending order</span>
+0160             <span class="keyword">end</span>
+0161             Wx = fliplr(Wx);    <span class="comment">% restore sorted eigenvectors into descending order</span>
+0162             
+0163             <span class="comment">% --- Calcualte Wy  ---</span>
+0164             
+0165             Wy = invCyy*Cyx*Wx;     <span class="comment">% Basis in Y</span>
+0166             <span class="comment">% Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy</span>
+0167             
+0168         <span class="keyword">end</span>
+0169         
+0170         
+0171         <a name="_sub7" href="#_subfunctions" class="code">function instancesOutput = extract(IT,sMatrix)</a>
+0172             
+0173             numClasses = length(IT.individualTemplates);
+0174             numInstances = size(sMatrix,1);
+0175             tempvec=zeros(numClasses,1);
+0176             instancesOutput = zeros(numInstances,numClasses);
+0177             <span class="keyword">for</span> i=1:numInstances
+0178                 <span class="keyword">for</span> j=1:numClasses
+0179                     [~,~,r1] = IT.cca(squeeze(sMatrix(i,:,:)),IT.individualTemplates{j});
+0180                     <span class="comment">%                     [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),IT.individualTemplates{j});</span>
+0181                     instancesOutput(i,j) = max(r1);
+0182                 <span class="keyword">end</span>
+0183             <span class="keyword">end</span>
+0184             
+0185             <span class="comment">%             [v,idx]=max(tempvec);</span>
+0186             <span class="comment">%             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;</span>
+0187             <span class="comment">%             if idx==j</span>
+0188             <span class="comment">%                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;</span>
+0189             <span class="comment">%             end</span>
+0190             <span class="comment">%</span>
+0191             <span class="comment">%             [numTrials,numChannels,~] = size(sMatrix);</span>
+0192             <span class="comment">%             sMatrix = permute(sMatrix,[3,2,1]);</span>
+0193             <span class="comment">%             for i=1:size(sMatrix,3);</span>
+0194             <span class="comment">%                 sMatrix(:,:,i) = (CSP.cspFilter*sMatrix(:,:,i)')';</span>
+0195             <span class="comment">%             end</span>
+0196             <span class="comment">%             instances = zeros(numTrials,numChannels);</span>
+0197             <span class="comment">%             for i=1:numTrials</span>
+0198             <span class="comment">%                 projectedTrial = sMatrix(:,:,i);</span>
+0199             <span class="comment">%                 variances = var(projectedTrial,0,1);</span>
+0200             <span class="comment">%                 instances(i,:) = log(variances)';</span>
+0201             <span class="comment">%             end</span>
+0202             <span class="comment">%             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);</span>
+0203         <span class="keyword">end</span>
+0204     <span class="keyword">end</span>
+0205 <span class="keyword">end</span>
+0206</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.m b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.m
new file mode 100644
index 0000000..2ff83dd
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.m
@@ -0,0 +1,206 @@
+classdef ITCCA < eegtoolkit.classification.ClassifierBase;
+    %                 instanceStruct = struct('sMatrix',sMatrix, 'labels', labels);
+    %     it=cell(12,1);
+    %                         for iN = 1:nClasses
+    %                             it{iN} = mean(SSVEPdata(chan_used,1:TW_p(tw_length),idx_traindata,iN),3);
+    %                         end
+    %                         % recognize SSVEP
+    %                         for j=1:nClasses
+    %                             tempvec=zeros(nClasses,1);
+    %                             for jj=1:nClasses
+    %                                 [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));
+    %                                 tempvec(jj) = max(r1);
+    %                             end
+    %
+    %                             [v,idx]=max(tempvec);
+    %                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;
+    %                             if idx==j
+    %                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;
+    %                             end
+    %                         end
+    properties (Constant)
+        
+    end
+    properties
+        baseClassifier;
+        individualTemplates;
+    end
+    
+    methods (Access = public)
+        function IT = ITCCA(instanceSet)
+            %             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')
+            %                 CSP.instanceSet = instanceSet;
+            %             else
+            %                 error('RawSignal extractor should be used with CSPWrapper');
+            %             end
+        end
+        
+        
+        function IT = build(IT)
+            % Builds the classification models
+            %             IT.learnCSPMatrix(IT.instanceSet.sMatrix,IT.instanceSet.labels);
+            numLabels = length(unique(IT.instanceSet.labels));
+            IT.individualTemplates = cell(numLabels,1);
+            unLabels = unique(IT.instanceSet.labels);
+            for i = 1:numLabels
+                trialsIndices = IT.instanceSet.labels==unLabels(i);
+                IT.individualTemplates{i} = squeeze(mean(IT.instanceSet.sMatrix(trialsIndices,:,:),1));
+            end
+            %             instances = IT.extract(IT.instanceSet.sMatrix);
+            %             instanceSet = eegtoolkit.util.InstanceSet(instances,IT.instanceSet.labels);
+            %             IT.baseClassifier.instanceSet = instanceSet;
+            %             IT.baseClassifier.build();
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(CSP,instance)
+            %                         for j=1:nClasses
+            %                             tempvec=zeros(nClasses,1);
+            %                             for jj=1:nClasses
+            %                                 [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),it{jj}(:,1:TW_p(tw_length)));
+            %                                 tempvec(jj) = max(r1);
+            %                             end
+            %
+            %                             [v,idx]=max(tempvec);
+            %                             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;
+            %                             if idx==j
+            %                                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;
+            %                             end
+            %                         end
+            %             instance = CSP.extract
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            testInstances = CSP.extract(instance);
+            [output, probabilities, ranking] = CSP.baseClassifier.classifyInstance(testInstances);
+            %             numModels = length(LSVM.models);
+            %             [numinstance, ~] = size(testInstances);
+            %             scores = zeros(numModels,numinstance);
+            %             for i=1:numModels
+            %                 %predict using the stored models
+            %                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');
+            %                 %store probability for each class
+            %                 scores(i,:) = t(:,1);
+            %             end
+            %             output = zeros(numinstance,1);
+            %             probabilities = zeros(numinstance,1);
+            %             ranking = scores;
+            %             for i=1:numinstance
+            %                 %select the class with the highest probability
+            %                 [prob, idx] = max(scores(:,i));
+            %                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+            %                 %output the label with highest probability
+            %                 output(i,1) = uniqueLabels(idx);
+            %                 %return the probability for the output label
+            %                 probabilities(i,1) = prob;
+            %             end
+        end
+        
+        function CSP = reset(CSP)
+            % 'Resets' the classifier.
+            %             CSP.models = {};
+        end
+        
+        function configInfo = getConfigInfo(CSP)
+            configInfo = '\n';
+        end
+        
+        
+        function time = getTime(CSP)
+            time = 0;
+        end
+    end
+    
+    
+    methods (Access = private)
+        function [Wx, Wy, r] = cca(CCA,X,Y)
+            %
+            % CCA calculate canonical correlations
+            %
+            % [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation
+            
+            % vectors as columns and r is a vector with corresponding canonical
+            % correlations. The correlations are sorted in descending order. X and Y
+            % are matrices where each column is a sample. Hence, X and Y must have
+            % the same number of columns.
+            %
+            % Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is
+            % then M*L, Wy is N*L and r is L*1.
+            %
+            %
+            % ?? 2000 Magnus Borga, Link?pings universitet
+            
+            % --- Calculate covariance matrices ---??????????????
+            
+            z = [X;Y];
+            C = cov(z.');
+            sx = size(X,1);   %X??????(??),
+            sy = size(Y,1);
+            Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+            Cxy = C(1:sx, sx+1:sx+sy);
+            Cyx = Cxy';
+            Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);%eye()????????
+            invCyy = inv(Cyy);
+            
+            % --- Calcualte Wx and r ---
+            
+            [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); % Basis in X eig????????????
+            r = sqrt(real(r));      % Canonical correlations
+            
+            % --- Sort correlations ---
+            
+            V = fliplr(Wx);		% reverse order of eigenvectors??????????????????????i??????????i??????
+            r = flipud(diag(r));	% extract eigenvalues and reverse their order
+            [r,I]= sort((real(r)));	% sort reversed eigenvalues in ascending order
+            r = flipud(r);		% restore sorted eigenvalues into descending order??????????????
+            for j = 1:length(I)
+                Wx(:,j) = V(:,I(j));  % sort reversed eigenvectors in ascending order
+            end
+            Wx = fliplr(Wx);	% restore sorted eigenvectors into descending order
+            
+            % --- Calcualte Wy  ---
+            
+            Wy = invCyy*Cyx*Wx;     % Basis in Y
+            % Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy
+            
+        end
+        
+        
+        function instancesOutput = extract(IT,sMatrix)
+            
+            numClasses = length(IT.individualTemplates);
+            numInstances = size(sMatrix,1);
+            tempvec=zeros(numClasses,1);
+            instancesOutput = zeros(numInstances,numClasses);
+            for i=1:numInstances
+                for j=1:numClasses
+                    [~,~,r1] = IT.cca(squeeze(sMatrix(i,:,:)),IT.individualTemplates{j});
+                    %                     [wx1,wy1,r1]=cca(SSVEPdata(chan_used,1:TW_p(tw_length),run,j),IT.individualTemplates{j});
+                    instancesOutput(i,j) = max(r1);
+                end
+            end
+            
+            %             [v,idx]=max(tempvec);
+            %             sub_lab(mth,(run-1)*nClasses+j,tw_length)=idx;
+            %             if idx==j
+            %                 n_correct(tw_length,mth)=n_correct(tw_length,mth)+1;
+            %             end
+            %
+            %             [numTrials,numChannels,~] = size(sMatrix);
+            %             sMatrix = permute(sMatrix,[3,2,1]);
+            %             for i=1:size(sMatrix,3);
+            %                 sMatrix(:,:,i) = (CSP.cspFilter*sMatrix(:,:,i)')';
+            %             end
+            %             instances = zeros(numTrials,numChannels);
+            %             for i=1:numTrials
+            %                 projectedTrial = sMatrix(:,:,i);
+            %                 variances = var(projectedTrial,0,1);
+            %                 instances(i,:) = log(variances)';
+            %             end
+            %             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/graph.dot b/doc/+eegtoolkit/+classification/@ITCCA/graph.dot
new file mode 100644
index 0000000..c21624b
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ITCCA -> ITCCA;
+
+  ITCCA [URL="ITCCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/graph.html b/doc/+eegtoolkit/+classification/@ITCCA/graph.html
new file mode 100644
index 0000000..986bd8d
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@ITCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@ITCCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@ITCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ITCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@ITCCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@ITCCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ITCCA.html" title="ITCCA" alt="" coords="104,29,102,22,95,15,84,10,70,7,55,5,39,7,26,10,15,15,8,22,5,29,8,37,15,43,26,49,39,52,55,53,70,52,84,49,95,43,102,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/graph.map b/doc/+eegtoolkit/+classification/@ITCCA/graph.map
new file mode 100644
index 0000000..3226b8d
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="ITCCA.html" title="ITCCA" alt="" coords="104,29,102,22,95,15,84,10,70,7,55,5,39,7,26,10,15,15,8,22,5,29,8,37,15,43,26,49,39,52,55,53,70,52,84,49,95,43,102,37">
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/graph.png b/doc/+eegtoolkit/+classification/@ITCCA/graph.png
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diff --git a/doc/+eegtoolkit/+classification/@ITCCA/index.html b/doc/+eegtoolkit/+classification/@ITCCA/index.html
new file mode 100644
index 0000000..a9f9e7b
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@ITCCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@ITCCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@ITCCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@ITCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ITCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@ITCCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ITCCA.html">ITCCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.html b/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.html
new file mode 100644
index 0000000..05b37d7
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.html
@@ -0,0 +1,289 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of L1MCCA</title>
+  <meta name="keywords" content="L1MCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@L1MCCA</a> &gt; L1MCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>L1MCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="L1MCCA.html" class="code" title="">L1MCCA</a>	</li><li><a href="../../../+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html" class="code" title="">L1MCCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="L1MCCA.html" class="code" title="">L1MCCA</a>	</li><li><a href="../../../+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html" class="code" title="">L1MCCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function L1MCCA = L1MCCA(samplingRate,numSeconds,numHarmonics,stimulusFrequencies)</a></li><li><a href="#_sub2" class="code">function L1MCCA = build(L1MCCA)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(L1MCCA,instance)</a></li><li><a href="#_sub4" class="code">function L1MCCA = reset(L1MCCA)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(L1MCCA)</a></li><li><a href="#_sub6" class="code">function [Wx, Wy, r] = cca(L1MCCA,X,Y)</a></li><li><a href="#_sub7" class="code">function  [w1,w3,v1] = smcca(L1MCCA,refdata,traindata,max_iter,iniw3,n_comp,lmbda)</a></li><li><a href="#_sub8" class="code">function y=squarewave(L1MCCA,f, S, T, H)</a></li><li><a href="#_sub9" class="code">function time = getTime(L1MCCA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="L1MCCA.m">L1MCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="L1MCCA.html" class="code" title="">L1MCCA</a>&lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004         
+0005     <span class="keyword">end</span>
+0006     properties
+0007         samplingRate;
+0008         numHarmonics;
+0009         numSeconds;
+0010         stimulusFrequencies;
+0011         models;
+0012         maxIterations;
+0013         nProjectionComponents;
+0014         lambda;
+0015     <span class="keyword">end</span>
+0016     
+0017     properties (Access = private)
+0018         referenceSignals;
+0019         optimalReferenceSignals;
+0020         projections;
+0021     <span class="keyword">end</span>
+0022     
+0023     methods (Access = public)
+0024         <a name="_sub0" href="#_subfunctions" class="code">function L1MCCA = L1MCCA(samplingRate,numSeconds,numHarmonics,stimulusFrequencies)</a>
+0025             L1MCCA.samplingRate = samplingRate;
+0026             L1MCCA.numSeconds = numSeconds;
+0027             L1MCCA.numHarmonics = numHarmonics;
+0028             L1MCCA.stimulusFrequencies = stimulusFrequencies;
+0029             
+0030             L1MCCA.maxIterations = 200;
+0031             L1MCCA.nProjectionComponents = 1;
+0032             L1MCCA.lambda = 0.02;
+0033             
+0034             L1MCCA.referenceSignals = {};
+0035             L1MCCA.projections = {};
+0036             L1MCCA.optimalReferenceSignals = {};
+0037             
+0038         <span class="keyword">end</span>
+0039         
+0040         <a name="_sub1" href="#_subfunctions" class="code">function L1MCCA = build(L1MCCA)</a>
+0041             L1MCCA.reset;
+0042             n_sti = length(L1MCCA.stimulusFrequencies);
+0043             TW = 0.5:0.5:L1MCCA.numSeconds;
+0044             TW_p = round(TW*L1MCCA.samplingRate);
+0045             
+0046             <span class="keyword">for</span> i=1:n_sti
+0047                 L1MCCA.referenceSignals{i} = L1MCCA.squarewave(L1MCCA.stimulusFrequencies(i)<span class="keyword">...</span>
+0048                     ,L1MCCA.samplingRate,L1MCCA.numSeconds*L1MCCA.samplingRate,L1MCCA.numHarmonics);
+0049             <span class="keyword">end</span>
+0050             <span class="keyword">for</span> i=1:n_sti
+0051                 a = L1MCCA.instanceSet.matrix4D(:,:,L1MCCA.instanceSet.labelss==i);
+0052                 [~,~,numIns] = size(a);
+0053                 iniw3 = ones(numIns,1);
+0054                 L1MCCA.projections{i} = {};
+0055                 [L1MCCA.projections{i}{1},L1MCCA.projections{i}{2},L1MCCA.projections{i}{3}] = L1MCCA.smcca(L1MCCA.referenceSignals{i},<span class="keyword">...</span>
+0056                     a,L1MCCA.maxIterations,iniw3,L1MCCA.nProjectionComponents,L1MCCA.lambda);
+0057             <span class="keyword">end</span>
+0058             <span class="keyword">for</span> i=1:n_sti
+0059                 L1MCCA.optimalReferenceSignals{i} = ttm(tensor(L1MCCA.instanceSet.matrix4D(:,:,L1MCCA.instanceSet.labelss==i)),L1MCCA.projections{i}{2}',3);
+0060                 L1MCCA.optimalReferenceSignals{i} = tenmat(L1MCCA.optimalReferenceSignals{i},1);
+0061                 L1MCCA.optimalReferenceSignals{i} = L1MCCA.optimalReferenceSignals{i}.data;
+0062                 L1MCCA.optimalReferenceSignals{i} = L1MCCA.projections{i}{1}'*L1MCCA.optimalReferenceSignals{i};
+0063             <span class="keyword">end</span>
+0064         <span class="keyword">end</span>
+0065         
+0066         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(L1MCCA,instance)</a>
+0067             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0068             <span class="comment">%output = predicted class</span>
+0069             <span class="comment">%probabilities = probability for predicted class</span>
+0070             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0071             
+0072             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0073             [~, ~,numInstance] = size(instance);
+0074             numLabels = length(L1MCCA.optimalReferenceSignals);
+0075             output = zeros(numInstance,1);
+0076             scores = zeros(numLabels,numInstance);
+0077             <span class="keyword">for</span> i=1:numInstance
+0078                 <span class="keyword">for</span> j=1:numLabels
+0079                     [~,~,r] = L1MCCA.cca(instance(:,:,i),L1MCCA.optimalReferenceSignals{j});
+0080                     scores(j,i) = max(r);
+0081                     
+0082                 <span class="keyword">end</span>
+0083                 [~,output(i,1)] = max(scores(:,i));
+0084             <span class="keyword">end</span>
+0085             ranking = scores;
+0086             probabilities = max(scores);
+0087         <span class="keyword">end</span>
+0088         
+0089         <a name="_sub3" href="#_subfunctions" class="code">function L1MCCA = reset(L1MCCA)</a>
+0090 <span class="comment">%             'Resets' the classifier.</span>
+0091             L1MCCA.referenceSignals = {};
+0092             L1MCCA.projections = {};
+0093             L1MCCA.optimalReferenceSignals = {};
+0094         <span class="keyword">end</span>
+0095         
+0096         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(L1MCCA)</a>
+0097             <span class="comment">% Prints the parameters of the classifier</span>
+0098             configInfo = <span class="string">'L1MCCA'</span>;
+0099         <span class="keyword">end</span>
+0100         
+0101         <a name="_sub5" href="#_subfunctions" class="code">function [Wx, Wy, r] = cca(L1MCCA,X,Y)</a>
+0102             
+0103             <span class="comment">% CCA calculate canonical correlations</span>
+0104             <span class="comment">%</span>
+0105             <span class="comment">% [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation</span>
+0106             <span class="comment">% vectors as columns and r is a vector with corresponding canonical</span>
+0107             <span class="comment">% correlations. The correlations are sorted in descending order. X and Y</span>
+0108             <span class="comment">% are matrices where each column is a sample. Hence, X and Y must have</span>
+0109             <span class="comment">% the same number of columns.</span>
+0110             <span class="comment">%</span>
+0111             <span class="comment">% Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is</span>
+0112             <span class="comment">% then M*L, Wy is N*L and r is L*1.</span>
+0113             <span class="comment">%</span>
+0114             <span class="comment">%</span>
+0115             <span class="comment">% ?? 2000 Magnus Borga, Link?pings universitet</span>
+0116             
+0117             <span class="comment">% --- Calculate covariance matrices ---</span>
+0118             
+0119             z = [X;Y];
+0120             C = cov(z.');
+0121             sx = size(X,1);
+0122             sy = size(Y,1);
+0123             Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+0124             Cxy = C(1:sx, sx+1:sx+sy);
+0125             Cyx = Cxy';
+0126             Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);
+0127             invCyy = inv(Cyy);
+0128             
+0129             <span class="comment">% --- Calcualte Wx and r ---</span>
+0130             
+0131             [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); <span class="comment">% Basis in X</span>
+0132             r = sqrt(real(r));      <span class="comment">% Canonical correlations</span>
+0133             
+0134             <span class="comment">% --- Sort correlations ---</span>
+0135             
+0136             V = fliplr(Wx);        <span class="comment">% reverse order of eigenvectors</span>
+0137             r = flipud(diag(r));    <span class="comment">% extract eigenvalues and reverse their order</span>
+0138             [r,I]= sort((real(r)));    <span class="comment">% sort reversed eigenvalues in ascending order</span>
+0139             r = flipud(r);        <span class="comment">% restore sorted eigenvalues into descending order</span>
+0140             <span class="keyword">for</span> j = 1:length(I)
+0141                 Wx(:,j) = V(:,I(j));  <span class="comment">% sort reversed eigenvectors in ascending order</span>
+0142             <span class="keyword">end</span>
+0143             Wx = fliplr(Wx);    <span class="comment">% restore sorted eigenvectors into descending order</span>
+0144             
+0145             <span class="comment">% --- Calcualte Wy  ---</span>
+0146             
+0147             Wy = invCyy*Cyx*Wx;     <span class="comment">% Basis in Y</span>
+0148             <span class="comment">% Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy</span>
+0149         <span class="keyword">end</span>
+0150         <a name="_sub6" href="#_subfunctions" class="code">function  [w1,w3,v1] = smcca(L1MCCA,refdata,traindata,max_iter,iniw3,n_comp,lmbda)</a>
+0151             <span class="comment">% L1-regualrized (Sparse) Multiway CCA</span>
+0152             <span class="comment">% traindata:    channel x time x trial</span>
+0153             <span class="comment">% refdata:      references by sine-cosine waveforms</span>
+0154             <span class="comment">%</span>
+0155             <span class="comment">% Rerefence:</span>
+0156             <span class="comment">% [1] Y. Zhang, G. Zhou, J. Jin, M. Wang, X. Wang, A. Cichocki.</span>
+0157             <span class="comment">%     L1-regularized multiway canonical correlation analysis for SSVEP-based BCI.</span>
+0158             <span class="comment">%     IEEE Trans. Neural Syst. Rehabil. Eng., 21(6): 887-896 (2013)</span>
+0159             <span class="comment">% [2] T.K. Kim, R. Cipolla. Canonical correlation analysis of video volume tensor for</span>
+0160             <span class="comment">%     action categorization and detection. IEEE Trans. PAMI, 31(8): 1415-1428 (2009)</span>
+0161             <span class="comment">%</span>
+0162             <span class="comment">%</span>
+0163             <span class="comment">% by Yu Zhang, ECUST, 2014.4.29</span>
+0164             <span class="comment">%</span>
+0165             
+0166             iter=1;
+0167             w3=iniw3;
+0168             w3=w3./norm(w3);
+0169             traindata=tensor(traindata);
+0170             refdata=tensor(refdata);
+0171             
+0172             er=0.00001;     <span class="comment">% error for iteration stop</span>
+0173             
+0174             <span class="keyword">while</span> iter&lt;max_iter
+0175                 projx3=ttm(traindata,w3',3);
+0176                 projx3=tenmat(projx3,1);                        <span class="comment">% unfolding each trial tensor into i-mode matrix</span>
+0177                 projx3=projx3.data;
+0178                 [v1,w1,r1]=L1MCCA.cca(refdata.data,projx3);
+0179                 v1=v1(:,1:n_comp); w1=w1(:,1:n_comp);
+0180                 v1=v1./norm(v1); w1=w1./norm(w1);
+0181                 projx1=ttm(traindata,w1',1);
+0182                 projx1=tenmat(projx1,3);                        <span class="comment">% unfolding each trial tensor into i-mode matrix</span>
+0183                 projx1=projx1.data;
+0184                 projref1=ttm(refdata,v1',1);
+0185                 projref1=projref1.data(:)';
+0186                 w3=lasso(projx1',projref1',<span class="string">'Lambda'</span>,lmbda);
+0187                 w3=w3./norm(w3);
+0188                 <span class="keyword">if</span> iter&gt;1
+0189                     <span class="keyword">if</span> all(sign(w1)==-sign(prew1))
+0190                         errw(1,iter-1)=norm(w1+prew1);
+0191                     <span class="keyword">else</span>
+0192                         errw(1,iter-1)=norm(w1-prew1);
+0193                     <span class="keyword">end</span>
+0194                     <span class="keyword">if</span> all(sign(w3)==-sign(prew3))
+0195                         errw(2,iter-1)=norm(w3+prew3);
+0196                     <span class="keyword">else</span>
+0197                         errw(2,iter-1)=norm(w3-prew3);
+0198                     <span class="keyword">end</span>
+0199                     <span class="keyword">if</span> all(sign(v1)==-sign(prev1))
+0200                         errw(3,iter-1)=norm(v1+prev1);
+0201                     <span class="keyword">else</span>
+0202                         errw(3,iter-1)=norm(v1-prev1);
+0203                     <span class="keyword">end</span>
+0204                     <span class="keyword">if</span> errw(1,iter-1)&lt;er &amp;&amp; errw(2,iter-1)&lt;er &amp;&amp; errw(3,iter-1)&lt;er
+0205                         <span class="keyword">break</span>
+0206                     <span class="keyword">end</span>
+0207                 <span class="keyword">end</span>
+0208                 prew1=w1;
+0209                 prew3=w3;
+0210                 prev1=v1;
+0211                 iter=iter+1;
+0212             <span class="keyword">end</span>
+0213             
+0214             fprintf(<span class="string">'L1MCCA Iteration is %d \n'</span>,iter);
+0215         <span class="keyword">end</span>
+0216         
+0217         
+0218         <a name="_sub7" href="#_subfunctions" class="code">function y=squarewave(L1MCCA,f, S, T, H)</a>
+0219             
+0220             <span class="comment">% f-- the fundermental frequency</span>
+0221             <span class="comment">% S-- the sampling rate</span>
+0222             <span class="comment">% T-- the number of sampling points</span>
+0223             <span class="comment">% H-- the number of harmonics</span>
+0224             
+0225             
+0226             <span class="keyword">for</span> i=1:H
+0227                 <span class="keyword">for</span> j=1:T
+0228                     t= j/S;
+0229                     y(2*i-1,j)=sin(2*pi*(i*f)*t);
+0230                     y(2*i,j)=cos(2*pi*(i*f)*t);
+0231                 <span class="keyword">end</span>
+0232             <span class="keyword">end</span>
+0233         <span class="keyword">end</span>
+0234         
+0235         <a name="_sub8" href="#_subfunctions" class="code">function time = getTime(L1MCCA)</a>
+0236             time = 0;
+0237         <span class="keyword">end</span>
+0238     <span class="keyword">end</span>
+0239 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.m b/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.m
new file mode 100644
index 0000000..3c65968
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/L1MCCA.m
@@ -0,0 +1,239 @@
+classdef L1MCCA< eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+        
+    end
+    properties
+        samplingRate;
+        numHarmonics;
+        numSeconds;
+        stimulusFrequencies;
+        models;
+        maxIterations;
+        nProjectionComponents;
+        lambda;
+    end
+    
+    properties (Access = private)
+        referenceSignals;
+        optimalReferenceSignals;
+        projections;
+    end
+    
+    methods (Access = public)
+        function L1MCCA = L1MCCA(samplingRate,numSeconds,numHarmonics,stimulusFrequencies)
+            L1MCCA.samplingRate = samplingRate;
+            L1MCCA.numSeconds = numSeconds;
+            L1MCCA.numHarmonics = numHarmonics;
+            L1MCCA.stimulusFrequencies = stimulusFrequencies;
+            
+            L1MCCA.maxIterations = 200;
+            L1MCCA.nProjectionComponents = 1;
+            L1MCCA.lambda = 0.02;
+            
+            L1MCCA.referenceSignals = {};
+            L1MCCA.projections = {};
+            L1MCCA.optimalReferenceSignals = {};
+            
+        end
+        
+        function L1MCCA = build(L1MCCA)
+            L1MCCA.reset;
+            n_sti = length(L1MCCA.stimulusFrequencies);
+            TW = 0.5:0.5:L1MCCA.numSeconds;
+            TW_p = round(TW*L1MCCA.samplingRate);
+            
+            for i=1:n_sti
+                L1MCCA.referenceSignals{i} = L1MCCA.squarewave(L1MCCA.stimulusFrequencies(i)...
+                    ,L1MCCA.samplingRate,L1MCCA.numSeconds*L1MCCA.samplingRate,L1MCCA.numHarmonics);
+            end
+            for i=1:n_sti
+                a = L1MCCA.instanceSet.matrix4D(:,:,L1MCCA.instanceSet.labelss==i);
+                [~,~,numIns] = size(a);
+                iniw3 = ones(numIns,1);
+                L1MCCA.projections{i} = {};
+                [L1MCCA.projections{i}{1},L1MCCA.projections{i}{2},L1MCCA.projections{i}{3}] = L1MCCA.smcca(L1MCCA.referenceSignals{i},...
+                    a,L1MCCA.maxIterations,iniw3,L1MCCA.nProjectionComponents,L1MCCA.lambda);
+            end
+            for i=1:n_sti
+                L1MCCA.optimalReferenceSignals{i} = ttm(tensor(L1MCCA.instanceSet.matrix4D(:,:,L1MCCA.instanceSet.labelss==i)),L1MCCA.projections{i}{2}',3);
+                L1MCCA.optimalReferenceSignals{i} = tenmat(L1MCCA.optimalReferenceSignals{i},1);
+                L1MCCA.optimalReferenceSignals{i} = L1MCCA.optimalReferenceSignals{i}.data;
+                L1MCCA.optimalReferenceSignals{i} = L1MCCA.projections{i}{1}'*L1MCCA.optimalReferenceSignals{i};
+            end
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(L1MCCA,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            [~, ~,numInstance] = size(instance);
+            numLabels = length(L1MCCA.optimalReferenceSignals);
+            output = zeros(numInstance,1);
+            scores = zeros(numLabels,numInstance);
+            for i=1:numInstance
+                for j=1:numLabels
+                    [~,~,r] = L1MCCA.cca(instance(:,:,i),L1MCCA.optimalReferenceSignals{j});
+                    scores(j,i) = max(r);
+                    
+                end
+                [~,output(i,1)] = max(scores(:,i));
+            end
+            ranking = scores;
+            probabilities = max(scores);
+        end
+        
+        function L1MCCA = reset(L1MCCA)
+%             'Resets' the classifier.
+            L1MCCA.referenceSignals = {};
+            L1MCCA.projections = {};
+            L1MCCA.optimalReferenceSignals = {};
+        end
+        
+        function configInfo = getConfigInfo(L1MCCA)
+            % Prints the parameters of the classifier
+            configInfo = 'L1MCCA';
+        end
+        
+        function [Wx, Wy, r] = cca(L1MCCA,X,Y)
+            
+            % CCA calculate canonical correlations
+            %
+            % [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation
+            % vectors as columns and r is a vector with corresponding canonical
+            % correlations. The correlations are sorted in descending order. X and Y
+            % are matrices where each column is a sample. Hence, X and Y must have
+            % the same number of columns.
+            %
+            % Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is
+            % then M*L, Wy is N*L and r is L*1.
+            %
+            %
+            % ?? 2000 Magnus Borga, Link?pings universitet
+            
+            % --- Calculate covariance matrices ---
+            
+            z = [X;Y];
+            C = cov(z.');
+            sx = size(X,1);
+            sy = size(Y,1);
+            Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+            Cxy = C(1:sx, sx+1:sx+sy);
+            Cyx = Cxy';
+            Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);
+            invCyy = inv(Cyy);
+            
+            % --- Calcualte Wx and r ---
+            
+            [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); % Basis in X
+            r = sqrt(real(r));      % Canonical correlations
+            
+            % --- Sort correlations ---
+            
+            V = fliplr(Wx);		% reverse order of eigenvectors
+            r = flipud(diag(r));	% extract eigenvalues and reverse their order
+            [r,I]= sort((real(r)));	% sort reversed eigenvalues in ascending order
+            r = flipud(r);		% restore sorted eigenvalues into descending order
+            for j = 1:length(I)
+                Wx(:,j) = V(:,I(j));  % sort reversed eigenvectors in ascending order
+            end
+            Wx = fliplr(Wx);	% restore sorted eigenvectors into descending order
+            
+            % --- Calcualte Wy  ---
+            
+            Wy = invCyy*Cyx*Wx;     % Basis in Y
+            % Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy
+        end
+        function  [w1,w3,v1] = smcca(L1MCCA,refdata,traindata,max_iter,iniw3,n_comp,lmbda)
+            % L1-regualrized (Sparse) Multiway CCA
+            % traindata:    channel x time x trial
+            % refdata:      references by sine-cosine waveforms
+            %
+            % Rerefence:
+            % [1] Y. Zhang, G. Zhou, J. Jin, M. Wang, X. Wang, A. Cichocki.
+            %     L1-regularized multiway canonical correlation analysis for SSVEP-based BCI.
+            %     IEEE Trans. Neural Syst. Rehabil. Eng., 21(6): 887-896 (2013)
+            % [2] T.K. Kim, R. Cipolla. Canonical correlation analysis of video volume tensor for
+            %     action categorization and detection. IEEE Trans. PAMI, 31(8): 1415-1428 (2009)
+            %
+            %
+            % by Yu Zhang, ECUST, 2014.4.29
+            %
+            
+            iter=1;
+            w3=iniw3;
+            w3=w3./norm(w3);
+            traindata=tensor(traindata);
+            refdata=tensor(refdata);
+            
+            er=0.00001;     % error for iteration stop
+            
+            while iter<max_iter
+                projx3=ttm(traindata,w3',3);
+                projx3=tenmat(projx3,1);                        % unfolding each trial tensor into i-mode matrix
+                projx3=projx3.data;
+                [v1,w1,r1]=L1MCCA.cca(refdata.data,projx3);
+                v1=v1(:,1:n_comp); w1=w1(:,1:n_comp);
+                v1=v1./norm(v1); w1=w1./norm(w1);
+                projx1=ttm(traindata,w1',1);
+                projx1=tenmat(projx1,3);                        % unfolding each trial tensor into i-mode matrix
+                projx1=projx1.data;
+                projref1=ttm(refdata,v1',1);
+                projref1=projref1.data(:)';
+                w3=lasso(projx1',projref1','Lambda',lmbda);
+                w3=w3./norm(w3);
+                if iter>1
+                    if all(sign(w1)==-sign(prew1))
+                        errw(1,iter-1)=norm(w1+prew1);
+                    else
+                        errw(1,iter-1)=norm(w1-prew1);
+                    end
+                    if all(sign(w3)==-sign(prew3))
+                        errw(2,iter-1)=norm(w3+prew3);
+                    else
+                        errw(2,iter-1)=norm(w3-prew3);
+                    end
+                    if all(sign(v1)==-sign(prev1))
+                        errw(3,iter-1)=norm(v1+prev1);
+                    else
+                        errw(3,iter-1)=norm(v1-prev1);
+                    end
+                    if errw(1,iter-1)<er && errw(2,iter-1)<er && errw(3,iter-1)<er
+                        break
+                    end
+                end
+                prew1=w1;
+                prew3=w3;
+                prev1=v1;
+                iter=iter+1;
+            end
+            
+            fprintf('L1MCCA Iteration is %d \n',iter);
+        end
+        
+        
+        function y=squarewave(L1MCCA,f, S, T, H)
+            
+            % f-- the fundermental frequency
+            % S-- the sampling rate
+            % T-- the number of sampling points
+            % H-- the number of harmonics
+            
+            
+            for i=1:H
+                for j=1:T
+                    t= j/S;
+                    y(2*i-1,j)=sin(2*pi*(i*f)*t);
+                    y(2*i,j)=cos(2*pi*(i*f)*t);
+                end
+            end
+        end
+        
+        function time = getTime(L1MCCA)
+            time = 0;
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/graph.dot b/doc/+eegtoolkit/+classification/@L1MCCA/graph.dot
new file mode 100644
index 0000000..5dff22f
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  L1MCCA -> L1MCCA;
+
+  L1MCCA [URL="L1MCCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/graph.html b/doc/+eegtoolkit/+classification/@L1MCCA/graph.html
new file mode 100644
index 0000000..73b2da2
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@L1MCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@L1MCCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@L1MCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@L1MCCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@L1MCCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="L1MCCA.html" title="L1MCCA" alt="" coords="129,29,126,22,117,15,103,10,86,7,67,5,47,7,30,10,16,15,7,22,4,29,7,37,16,43,30,49,47,52,67,53,86,52,103,49,117,43,126,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/graph.map b/doc/+eegtoolkit/+classification/@L1MCCA/graph.map
new file mode 100644
index 0000000..55100c7
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="L1MCCA.html" title="L1MCCA" alt="" coords="129,29,126,22,117,15,103,10,86,7,67,5,47,7,30,10,16,15,7,22,4,29,7,37,16,43,30,49,47,52,67,53,86,52,103,49,117,43,126,37">
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diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/index.html b/doc/+eegtoolkit/+classification/@L1MCCA/index.html
new file mode 100644
index 0000000..bb4d8ac
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@L1MCCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@L1MCCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@L1MCCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@L1MCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@L1MCCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="L1MCCA.html">L1MCCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LDA/LDA.html b/doc/+eegtoolkit/+classification/@LDA/LDA.html
new file mode 100644
index 0000000..e8c6922
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/LDA.html
@@ -0,0 +1,131 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of LDA</title>
+  <meta name="keywords" content="LDA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@LDA</a> &gt; LDA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>LDA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LDA.html" class="code" title="">LDA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LDA.html" class="code" title="">LDA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function LDA = LDA(instanceSet)</a></li><li><a href="#_sub2" class="code">function LDA = build(LDA)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(LDA,instance)</a></li><li><a href="#_sub4" class="code">function LDA = reset(LDA)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(LDA)</a></li><li><a href="#_sub6" class="code">function time = getTime(LDA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="LDA.m">LDA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="LDA.html" class="code" title="">LDA</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties (Access = public)
+0008       W_LDA;
+0009       PCA_mat;
+0010       trainFeat;
+0011     <span class="keyword">end</span>
+0012     
+0013     methods (Access = public)
+0014         <a name="_sub0" href="#_subfunctions" class="code">function LDA = LDA(instanceSet)</a>
+0015             <span class="keyword">if</span> nargin &gt; 0
+0016                 LDA.instanceSet = instanceSet;
+0017             <span class="keyword">end</span>
+0018            
+0019         <span class="keyword">end</span>
+0020         
+0021         <a name="_sub1" href="#_subfunctions" class="code">function LDA = build(LDA)</a>
+0022             LDA.reset();
+0023             data = LDA.instanceSet.getInstances;
+0024             data = data';  
+0025             labels = LDA.instanceSet.getLabels;   
+0026             unique(labels)           
+0027             numTrials = length(labels);
+0028 
+0029             PCA_W=pca_func(data);
+0030 <span class="comment">%             PCA_W=eye(8000);</span>
+0031             train_Data=PCA_W'*data; 
+0032             
+0033             Par.mode = <span class="string">'LDA'</span>;
+0034             dim = length(unique(labels))-1;
+0035             [W,Wp] = SGE_GraphConstruct(labels,Par);
+0036             [TransMatrix,~] = SGE_Mapping(train_Data,dim,W,Wp);
+0037             LDA.W_LDA = TransMatrix;
+0038             LDA.PCA_mat=PCA_W;
+0039             mtrainFeat=SGE_Projection(train_Data,1:dim,TransMatrix);
+0040             LDA.trainFeat=mtrainFeat;                       
+0041 <span class="comment">%             figure,gplotmatrix(mtrainFeat',[],labels)</span>
+0042         <span class="keyword">end</span>
+0043         
+0044         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(LDA,instance)</a>
+0045             
+0046             N = size(instance,1);            
+0047             instance = instance'; 
+0048 
+0049             test_Data=LDA.PCA_mat'*instance;               
+0050 <span class="comment">%             test_Data=[ones(1,N);test_Data];</span>
+0051 
+0052             testFeat=LDA.W_LDA'*test_Data;  
+0053             X = LDA.trainFeat;
+0054             y = LDA.instanceSet.getLabels;
+0055             [~,output] = SGE_Classification(X,y',testFeat,0,<span class="string">'euc'</span>);
+0056             output = output(1,:)';
+0057             probabilities=zeros(N,1);
+0058             ranking=zeros(N,1);
+0059 <span class="comment">%             figure,gplotmatrix(testFeat',[],output)</span>
+0060           
+0061         <span class="keyword">end</span>
+0062         
+0063         <a name="_sub3" href="#_subfunctions" class="code">function LDA = reset(LDA)</a>
+0064             <span class="comment">%delete all stored models</span>
+0065             LDA.W_LDA=[];
+0066             LDA.PCA_mat=[];
+0067             LDA.trainFeat=[];
+0068         <span class="keyword">end</span>
+0069         
+0070         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(LDA)</a>
+0071             configInfo = sprintf(<span class="string">'MLR_Classifier'</span>);
+0072         <span class="keyword">end</span>
+0073         
+0074                         
+0075         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(LDA)</a>
+0076             
+0077         <span class="keyword">end</span>
+0078                 
+0079     <span class="keyword">end</span>
+0080 <span class="keyword">end</span>
+0081</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LDA/LDA.m b/doc/+eegtoolkit/+classification/@LDA/LDA.m
new file mode 100644
index 0000000..f5e762a
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/LDA.m
@@ -0,0 +1,81 @@
+classdef LDA < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties (Access = public)
+      W_LDA;
+      PCA_mat;
+      trainFeat;
+    end
+    
+    methods (Access = public)
+        function LDA = LDA(instanceSet)
+            if nargin > 0
+                LDA.instanceSet = instanceSet;
+            end
+           
+        end
+        
+        function LDA = build(LDA)
+            LDA.reset();
+            data = LDA.instanceSet.getInstances;
+            data = data';  
+            labels = LDA.instanceSet.getLabels;   
+            unique(labels)           
+            numTrials = length(labels);
+
+            PCA_W=pca_func(data);
+%             PCA_W=eye(8000);
+            train_Data=PCA_W'*data; 
+            
+            Par.mode = 'LDA';
+            dim = length(unique(labels))-1;
+            [W,Wp] = SGE_GraphConstruct(labels,Par);
+            [TransMatrix,~] = SGE_Mapping(train_Data,dim,W,Wp);
+            LDA.W_LDA = TransMatrix;
+            LDA.PCA_mat=PCA_W;
+            mtrainFeat=SGE_Projection(train_Data,1:dim,TransMatrix);
+            LDA.trainFeat=mtrainFeat;                       
+%             figure,gplotmatrix(mtrainFeat',[],labels)
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(LDA,instance)
+            
+            N = size(instance,1);            
+            instance = instance'; 
+
+            test_Data=LDA.PCA_mat'*instance;               
+%             test_Data=[ones(1,N);test_Data]; 
+
+            testFeat=LDA.W_LDA'*test_Data;  
+            X = LDA.trainFeat;
+            y = LDA.instanceSet.getLabels;
+            [~,output] = SGE_Classification(X,y',testFeat,0,'euc');
+            output = output(1,:)';
+            probabilities=zeros(N,1);
+            ranking=zeros(N,1);
+%             figure,gplotmatrix(testFeat',[],output)
+          
+        end
+        
+        function LDA = reset(LDA)
+            %delete all stored models 
+            LDA.W_LDA=[];
+            LDA.PCA_mat=[];
+            LDA.trainFeat=[];
+        end
+        
+        function configInfo = getConfigInfo(LDA)
+            configInfo = sprintf('MLR_Classifier');
+        end
+        
+                        
+        function time = getTime(LDA)
+            
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@LDA/graph.dot b/doc/+eegtoolkit/+classification/@LDA/graph.dot
new file mode 100644
index 0000000..89a5dcc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  LDA -> LDA;
+
+  LDA [URL="LDA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LDA/graph.html b/doc/+eegtoolkit/+classification/@LDA/graph.html
new file mode 100644
index 0000000..8c50b7b
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@LDA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@LDA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@LDA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@LDA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@LDA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="LDA.html" title="LDA" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LDA/graph.map b/doc/+eegtoolkit/+classification/@LDA/graph.map
new file mode 100644
index 0000000..85fcbaf
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="LDA.html" title="LDA" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
diff --git a/doc/+eegtoolkit/+classification/@LDA/graph.png b/doc/+eegtoolkit/+classification/@LDA/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+classification/@LDA/index.html b/doc/+eegtoolkit/+classification/@LDA/index.html
new file mode 100644
index 0000000..17ed76c
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LDA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@LDA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@LDA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@LDA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@LDA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="LDA.html">LDA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.html b/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.html
new file mode 100644
index 0000000..76995a2
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.html
@@ -0,0 +1,166 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of LIBSVM</title>
+  <meta name="keywords" content="LIBSVM">
+  <meta name="description" content="LIBSVMCLASSIFIER class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@LIBSVM</a> &gt; LIBSVM.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVM&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>LIBSVM
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>LIBSVMCLASSIFIER class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> LIBSVMCLASSIFIER class
+ Wrapper class of the libsvm library (libsvm) .mex files must be added to
+ your matlab path before using this class</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LIBSVM.html" class="code" title="">LIBSVM</a>	LIBSVMCLASSIFIER class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LIBSVM.html" class="code" title="">LIBSVM</a>	LIBSVMCLASSIFIER class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function LSVM = LIBSVM(instanceSet)</a></li><li><a href="#_sub2" class="code">function LSVM = build(LSVM)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(LSVM,instance)</a></li><li><a href="#_sub4" class="code">function LSVM = reset(LSVM)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(LSVM)</a></li><li><a href="#_sub6" class="code">function newLSVM = copy(LSVM)</a></li><li><a href="#_sub7" class="code">function time = getTime(LSVM)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="LIBSVM.m">LIBSVM.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 
+0002 <span class="comment">% LIBSVMCLASSIFIER class</span>
+0003 <span class="comment">% Wrapper class of the libsvm library (libsvm) .mex files must be added to</span>
+0004 <span class="comment">% your matlab path before using this class</span>
+0005 classdef <a href="LIBSVM.html" class="code" title="">LIBSVM</a> &lt; eegtoolkit.classification.ClassifierBase
+0006     
+0007     properties (Constant)
+0008         KERNEL_LINEAR = 0; 
+0009 <span class="comment">%         KERNEL_POLYNOMIAL = 1; not supported yet</span>
+0010         KERNEL_RBF = 2;
+0011 <span class="comment">%         KERNEL_SIGMOID = 3; not supported yet</span>
+0012     <span class="keyword">end</span>
+0013     properties
+0014         kernel; <span class="comment">% The svm kernel</span>
+0015         cost; <span class="comment">% The cost parameter</span>
+0016         gamma; <span class="comment">% The gamma parameter (used only with rbf kernel)</span>
+0017         models; <span class="comment">% The trained models</span>
+0018     <span class="keyword">end</span>
+0019     
+0020     methods (Access = public)
+0021         <a name="_sub0" href="#_subfunctions" class="code">function LSVM = LIBSVM(instanceSet)</a>
+0022             <span class="keyword">if</span> nargin &gt; 0
+0023                 LSVM.kernel = LSVM.KERNEL_LINEAR;
+0024                 LSVM.cost = 1.0;
+0025                 LSVM.instanceSet = instanceSet;
+0026                 LSVM.gamma = 1/instanceSet.getNumFeatures;
+0027             <span class="keyword">else</span>
+0028                 LSVM.kernel = LSVM.KERNEL_LINEAR;
+0029                 LSVM.cost = 1.0;
+0030                 LSVM.gamma = 1;
+0031             <span class="keyword">end</span>
+0032         <span class="keyword">end</span>
+0033         
+0034         <a name="_sub1" href="#_subfunctions" class="code">function LSVM = build(LSVM)</a>
+0035             <span class="comment">% Builds the classification models</span>
+0036             LSVM.reset;
+0037             numLabels = LSVM.instanceSet.getNumLabels;
+0038             uniqueLabels = unique(LSVM.instanceSet.getLabels);
+0039             <span class="keyword">for</span> i=1:numLabels
+0040                 currentLabel = uniqueLabels(i);
+0041                 labels = zeros(LSVM.instanceSet.getNumInstances,1)-1;
+0042                 labels(LSVM.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+0043                 instances = sparse(LSVM.instanceSet.getInstances);
+0044                 <span class="keyword">if</span> LSVM.kernel == LSVM.KERNEL_LINEAR;
+0045                     <span class="comment">%store the models in an instance variable</span>
+0046                     LSVM.models{i} = svmtrain(labels, instances, sprintf(<span class="string">'-t %d -c %f  -q'</span>, LSVM.kernel, LSVM.cost));
+0047                 <span class="keyword">elseif</span> LSVM.kernel == LSVM.KERNEL_RBF;
+0048                     LSVM.models{i} = svmtrain(labels, instances, sprintf(<span class="string">'-t %d -c %f -g %f  -q'</span>, LSVM.kernel, LSVM.cost, LSVM.gamma));
+0049                 <span class="keyword">else</span>
+0050                     error(<span class="string">'invalid kernel parameter'</span>);
+0051                 <span class="keyword">end</span>
+0052             <span class="keyword">end</span>
+0053         <span class="keyword">end</span>
+0054         
+0055         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(LSVM,instance)</a>
+0056             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0057             <span class="comment">%output = predicted class</span>
+0058             <span class="comment">%probabilities = probability for predicted class</span>
+0059             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0060             
+0061             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0062             numModels = length(LSVM.models);
+0063             [numinstance, ~] = size(instance);
+0064             scores = zeros(numModels,numinstance);
+0065             <span class="keyword">for</span> i=1:numModels
+0066                 <span class="comment">%predict using the stored models</span>
+0067                 [~, ~, t] = svmpredict(eye(numinstance,1),instance, LSVM.models{i},<span class="string">' -q'</span>);
+0068                 <span class="comment">%store probability for each class</span>
+0069                 scores(i,:) = t(:,1);
+0070             <span class="keyword">end</span>
+0071             output = zeros(numinstance,1);
+0072             probabilities = zeros(numinstance,1);
+0073             ranking = scores';
+0074             <span class="keyword">for</span> i=1:numinstance
+0075                 <span class="comment">%select the class with the highest probability</span>
+0076                 [prob, idx] = max(scores(:,i));
+0077                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+0078                 <span class="comment">%output the label with highest probability</span>
+0079                 output(i,1) = uniqueLabels(idx);
+0080                 <span class="comment">%return the probability for the output label</span>
+0081                 probabilities(i,1) = prob;
+0082             <span class="keyword">end</span>
+0083         <span class="keyword">end</span>
+0084         
+0085         <a name="_sub3" href="#_subfunctions" class="code">function LSVM = reset(LSVM)</a>
+0086             <span class="comment">% 'Resets' the classifier.</span>
+0087             LSVM.models = {};
+0088         <span class="keyword">end</span>
+0089         
+0090         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(LSVM)</a>
+0091             <span class="comment">% Prints the parameters of the classifier</span>
+0092             <span class="keyword">switch</span> LSVM.kernel
+0093                 <span class="keyword">case</span> LSVM.KERNEL_LINEAR
+0094                     configInfo = sprintf(<span class="string">'LIBSVM\tkernel:linear\tcost:%d'</span>, LSVM.cost);
+0095                 <span class="keyword">case</span> LSVM.KERNEL_RBF
+0096                     configInfo = sprintf(<span class="string">'LIBSVM\tkernel:rbf\tcost:%d\tgamma:%d'</span>, LSVM.cost, LSVM.gamma);
+0097                 <span class="keyword">otherwise</span> 
+0098                     configInfo = <span class="string">'Error in configuration (only linear and rbf kernels supported for now)'</span>;
+0099             <span class="keyword">end</span>
+0100         <span class="keyword">end</span>
+0101         
+0102         <a name="_sub5" href="#_subfunctions" class="code">function newLSVM = copy(LSVM)</a>
+0103             newLSVM = eegtoolkit.classification.LIBSVM;
+0104             newLSVM.kernel = LSVM.kernel;
+0105             newLSVM.cost = LSVM.cost;
+0106             newLSVM.gamma = LSVM.gamma;
+0107         <span class="keyword">end</span>
+0108         
+0109                         
+0110         <a name="_sub6" href="#_subfunctions" class="code">function time = getTime(LSVM)</a>
+0111             time = 0;
+0112         <span class="keyword">end</span>
+0113     <span class="keyword">end</span>
+0114 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.m b/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.m
new file mode 100644
index 0000000..1db8ec3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.m
@@ -0,0 +1,114 @@
+
+% LIBSVMCLASSIFIER class
+% Wrapper class of the libsvm library (libsvm) .mex files must be added to
+% your matlab path before using this class
+classdef LIBSVM < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+        KERNEL_LINEAR = 0; 
+%         KERNEL_POLYNOMIAL = 1; not supported yet
+        KERNEL_RBF = 2;
+%         KERNEL_SIGMOID = 3; not supported yet
+    end
+    properties
+        kernel; % The svm kernel
+        cost; % The cost parameter
+        gamma; % The gamma parameter (used only with rbf kernel)
+        models; % The trained models
+    end
+    
+    methods (Access = public)
+        function LSVM = LIBSVM(instanceSet)
+            if nargin > 0
+                LSVM.kernel = LSVM.KERNEL_LINEAR;
+                LSVM.cost = 1.0;
+                LSVM.instanceSet = instanceSet;
+                LSVM.gamma = 1/instanceSet.getNumFeatures;
+            else
+                LSVM.kernel = LSVM.KERNEL_LINEAR;
+                LSVM.cost = 1.0;
+                LSVM.gamma = 1;
+            end
+        end
+        
+        function LSVM = build(LSVM)
+            % Builds the classification models
+            LSVM.reset;
+            numLabels = LSVM.instanceSet.getNumLabels;
+            uniqueLabels = unique(LSVM.instanceSet.getLabels);
+            for i=1:numLabels
+                currentLabel = uniqueLabels(i);
+                labels = zeros(LSVM.instanceSet.getNumInstances,1)-1;
+                labels(LSVM.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+                instances = sparse(LSVM.instanceSet.getInstances);
+                if LSVM.kernel == LSVM.KERNEL_LINEAR;
+                    %store the models in an instance variable
+                    LSVM.models{i} = svmtrain(labels, instances, sprintf('-t %d -c %f  -q', LSVM.kernel, LSVM.cost));
+                elseif LSVM.kernel == LSVM.KERNEL_RBF;
+                    LSVM.models{i} = svmtrain(labels, instances, sprintf('-t %d -c %f -g %f  -q', LSVM.kernel, LSVM.cost, LSVM.gamma));
+                else
+                    error('invalid kernel parameter');
+                end
+            end
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(LSVM,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(LSVM.models);
+            [numinstance, ~] = size(instance);
+            scores = zeros(numModels,numinstance);
+            for i=1:numModels
+                %predict using the stored models
+                [~, ~, t] = svmpredict(eye(numinstance,1),instance, LSVM.models{i},' -q');
+                %store probability for each class
+                scores(i,:) = t(:,1);
+            end
+            output = zeros(numinstance,1);
+            probabilities = zeros(numinstance,1);
+            ranking = scores';
+            for i=1:numinstance
+                %select the class with the highest probability
+                [prob, idx] = max(scores(:,i));
+                uniqueLabels = unique(LSVM.instanceSet.getLabels);
+                %output the label with highest probability
+                output(i,1) = uniqueLabels(idx);
+                %return the probability for the output label
+                probabilities(i,1) = prob;
+            end
+        end
+        
+        function LSVM = reset(LSVM)
+            % 'Resets' the classifier.
+            LSVM.models = {};
+        end
+        
+        function configInfo = getConfigInfo(LSVM)
+            % Prints the parameters of the classifier
+            switch LSVM.kernel
+                case LSVM.KERNEL_LINEAR
+                    configInfo = sprintf('LIBSVM\tkernel:linear\tcost:%d', LSVM.cost);
+                case LSVM.KERNEL_RBF
+                    configInfo = sprintf('LIBSVM\tkernel:rbf\tcost:%d\tgamma:%d', LSVM.cost, LSVM.gamma);
+                otherwise 
+                    configInfo = 'Error in configuration (only linear and rbf kernels supported for now)';
+            end
+        end
+        
+        function newLSVM = copy(LSVM)
+            newLSVM = eegtoolkit.classification.LIBSVM;
+            newLSVM.kernel = LSVM.kernel;
+            newLSVM.cost = LSVM.cost;
+            newLSVM.gamma = LSVM.gamma;
+        end
+        
+                        
+        function time = getTime(LSVM)
+            time = 0;
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/graph.dot b/doc/+eegtoolkit/+classification/@LIBSVM/graph.dot
new file mode 100644
index 0000000..94bc240
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVM/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  LIBSVM -> LIBSVM;
+
+  LIBSVM [URL="LIBSVM.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/graph.html b/doc/+eegtoolkit/+classification/@LIBSVM/graph.html
new file mode 100644
index 0000000..07b031c
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVM/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@LIBSVM</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@LIBSVM">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@LIBSVM">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVM&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@LIBSVM</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@LIBSVM" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="LIBSVM.html" title="LIBSVM" alt="" coords="123,29,120,22,112,15,99,10,82,7,64,5,46,7,29,10,16,15,8,22,5,29,8,37,16,43,29,49,46,52,64,53,82,52,99,49,112,43,120,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/graph.map b/doc/+eegtoolkit/+classification/@LIBSVM/graph.map
new file mode 100644
index 0000000..01d58f1
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVM/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/index.html b/doc/+eegtoolkit/+classification/@LIBSVM/index.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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+  <title>Index for Directory ./+eegtoolkit/+classification/@LIBSVM</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@LIBSVM">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@LIBSVM">
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+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVM&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@LIBSVM</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="LIBSVM.html">LIBSVM</a></td><td>LIBSVMCLASSIFIER class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/LIBSVMFast.html b/doc/+eegtoolkit/+classification/@LIBSVMFast/LIBSVMFast.html
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@@ -0,0 +1,174 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of LIBSVMFast</title>
+  <meta name="keywords" content="LIBSVMFast">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
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+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@LIBSVMFast</a> &gt; LIBSVMFast.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVMFast&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>LIBSVMFast
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LIBSVMFast.html" class="code" title="">LIBSVMFast</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LIBSVMFast.html" class="code" title="">LIBSVMFast</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function LSVM = LIBSVMFast (instanceSet,kernel,cost,gamma,maxlag,scaleopt)</a></li><li><a href="#_sub2" class="code">function LSVM = build(LSVM)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(LSVM)</a></li><li><a href="#_sub4" class="code">function LSVM = reset(LSVM)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(LSVM)</a></li><li><a href="#_sub6" class="code">function time = getTime(LSVM)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="LIBSVMFast.m">LIBSVMFast.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="LIBSVMFast.html" class="code" title="">LIBSVMFast</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     properties
+0007         kernel;
+0008         cost;
+0009         gamma;
+0010         models;
+0011         Ktrain;
+0012         Ktest;
+0013         maxlag;
+0014         scaleopt;
+0015         predictTotalTime;
+0016         predictCount;
+0017     <span class="keyword">end</span>
+0018     
+0019     methods (Access = public)
+0020         <a name="_sub0" href="#_subfunctions" class="code">function LSVM = LIBSVMFast (instanceSet,kernel,cost,gamma,maxlag,scaleopt)</a>
+0021             <span class="comment">%set default parameters</span>
+0022             LSVM.predictTotalTime = 0;
+0023             LSVM.predictCount = 0;
+0024             LSVM.kernel = <span class="string">'linear'</span>;
+0025             LSVM.cost = 1.0;
+0026             LSVM.gamma = 0.01;
+0027             LSVM.maxlag = 150;
+0028             LSVM.scaleopt = <span class="string">'coeff'</span>;
+0029             <span class="keyword">if</span> nargin &gt; 0
+0030                 LSVM.instanceSet = instanceSet;
+0031                 LSVM.gamma = 1/instanceSet.getNumFeatures;
+0032             <span class="keyword">end</span>
+0033             <span class="keyword">if</span> nargin &gt; 1
+0034                 LSVM.kernel = kernel;
+0035             <span class="keyword">end</span>
+0036             <span class="keyword">if</span> nargin &gt; 2
+0037                 LSVM.cost = cost;
+0038             <span class="keyword">end</span>
+0039             <span class="keyword">if</span> nargin &gt; 3
+0040                 LSVM.gamma = gamma;
+0041             <span class="keyword">end</span>
+0042             <span class="keyword">if</span> nargin &gt; 4
+0043                 LSVM.maxlag = maxlag;
+0044             <span class="keyword">end</span>
+0045             <span class="keyword">if</span> nargin &gt; 5
+0046                 LSVM.scaleopt = scaleopt;
+0047             <span class="keyword">end</span>
+0048         <span class="keyword">end</span>
+0049         
+0050         <a name="_sub1" href="#_subfunctions" class="code">function LSVM = build(LSVM)</a>
+0051             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0052             LSVM.reset;
+0053             numLabels = LSVM.instanceSet.getNumLabels;
+0054             uniqueLabels = unique(LSVM.instanceSet.getLabels);
+0055             <span class="keyword">for</span> i=1:numLabels
+0056                 currentLabel = uniqueLabels(i);
+0057                 labels = zeros(LSVM.instanceSet.getNumInstances,1)-1;
+0058                 labels(LSVM.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+0059                 LSVM.models{i} = svmtrain(labels, [(1:size(LSVM.Ktrain,1))', <span class="keyword">...</span>
+0060                     LSVM.Ktrain+eye(size(LSVM.Ktrain,1))*realmin], <span class="keyword">...</span>
+0061                     sprintf(<span class="string">' -t 4 -c %f -b 1 -q'</span>, LSVM.cost));
+0062             <span class="keyword">end</span>
+0063         <span class="keyword">end</span>
+0064         
+0065         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(LSVM)</a>
+0066             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0067             <span class="comment">%output = predicted class</span>
+0068             <span class="comment">%probabilities = probability for predicted class</span>
+0069             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0070             
+0071             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0072             numModels = length(LSVM.models);
+0073             [numinstance, ~] = size(LSVM.Ktest);
+0074             scores = zeros(numModels,numinstance);
+0075             <span class="keyword">for</span> i=1:numModels
+0076                 <span class="comment">%predict using the stored models</span>
+0077                 tic
+0078                 [~, ~, t] = svmpredict(eye(numinstance,1),<span class="keyword">...</span>
+0079                     [(1:numinstance)', LSVM.Ktest], LSVM.models{i},<span class="string">'-b 1 -q'</span>);
+0080                 LSVM.predictTotalTime = LSVM.predictTotalTime + toc;
+0081                 LSVM.predictCount = LSVM.predictCount + numinstance;
+0082                 <span class="comment">%svmpredict(labels(~idx), [(1:sum(~idx))', K(~idx,idx)], model);</span>
+0083                 <span class="comment">%store probability for each class</span>
+0084                 scores(i,:) = t(:,1);
+0085             <span class="keyword">end</span>
+0086             output = zeros(numinstance,1);
+0087             probabilities = zeros(numinstance,1);
+0088             <span class="comment">%we need these for ranking metrics (e.g. mAP)</span>
+0089             ranking = scores;
+0090             <span class="keyword">for</span> i=1:numinstance
+0091                 <span class="comment">%select the class with the highest probability</span>
+0092                 [prob, idx] = max(scores(:,i));
+0093                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+0094                 <span class="comment">%output the label with highest probability</span>
+0095                 output(i,1) = uniqueLabels(idx);
+0096                 <span class="comment">%return the probability for the output label</span>
+0097                 probabilities(i,1) = prob;
+0098             <span class="keyword">end</span>
+0099         <span class="keyword">end</span>
+0100         
+0101         <a name="_sub3" href="#_subfunctions" class="code">function LSVM = reset(LSVM)</a>
+0102             <span class="comment">%delete all stored models</span>
+0103             LSVM.models = {};
+0104         <span class="keyword">end</span>
+0105         
+0106         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(LSVM)</a>
+0107             <span class="keyword">switch</span> LSVM.kernel
+0108                 <span class="keyword">case</span> {<span class="string">'linear'</span>,<span class="string">'spearman'</span>,<span class="string">'correlation'</span>,<span class="string">'cosine'</span>}
+0109                     configInfo = sprintf(<span class="string">'LIBSVMFast\tkernel:%s\tcost:%d'</span>, LSVM.kernel, LSVM.cost);
+0110                 <span class="keyword">case</span> <span class="string">'xcorr'</span>
+0111                     configInfo = sprintf(<span class="string">'LIBSVMFast\tkernel:%s\tcost:%d\tgamma:%d\tmaxlag:%d\tscaleopt:%s'</span>, LSVM.kernel, LSVM.cost, LSVM.maxlag,LSVM.scaleopt);
+0112                 <span class="keyword">otherwise</span>
+0113                     configInfo = sprintf(<span class="string">'LIBSVMFast\tkernel:%s\tcost:%d\tgamma:%d'</span>, LSVM.kernel, LSVM.cost, LSVM.gamma);
+0114 <span class="comment">%                 otherwise</span>
+0115 <span class="comment">%                     configInfo = 'Error in configuration (only linear and rbf kernels supported for now)';</span>
+0116             <span class="keyword">end</span>
+0117         <span class="keyword">end</span>
+0118         
+0119         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(LSVM)</a>
+0120             time = LSVM.predictTotalTime/LSVM.predictCount;
+0121         <span class="keyword">end</span>
+0122     <span class="keyword">end</span>
+0123 <span class="keyword">end</span>
+0124</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/LIBSVMFast.m b/doc/+eegtoolkit/+classification/@LIBSVMFast/LIBSVMFast.m
new file mode 100644
index 0000000..429d32f
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVMFast/LIBSVMFast.m
@@ -0,0 +1,124 @@
+classdef LIBSVMFast < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    properties
+        kernel;
+        cost;
+        gamma;
+        models;
+        Ktrain;
+        Ktest;
+        maxlag;
+        scaleopt;
+        predictTotalTime;
+        predictCount;
+    end
+    
+    methods (Access = public)
+        function LSVM = LIBSVMFast (instanceSet,kernel,cost,gamma,maxlag,scaleopt)
+            %set default parameters
+            LSVM.predictTotalTime = 0;
+            LSVM.predictCount = 0;
+            LSVM.kernel = 'linear';
+            LSVM.cost = 1.0;
+            LSVM.gamma = 0.01;
+            LSVM.maxlag = 150;
+            LSVM.scaleopt = 'coeff';
+            if nargin > 0
+                LSVM.instanceSet = instanceSet;
+                LSVM.gamma = 1/instanceSet.getNumFeatures;
+            end
+            if nargin > 1
+                LSVM.kernel = kernel;
+            end
+            if nargin > 2
+                LSVM.cost = cost;
+            end
+            if nargin > 3
+                LSVM.gamma = gamma;
+            end
+            if nargin > 4
+                LSVM.maxlag = maxlag;
+            end
+            if nargin > 5
+                LSVM.scaleopt = scaleopt;
+            end
+        end
+        
+        function LSVM = build(LSVM)
+            %clear all from previous calls to "build"
+            LSVM.reset;
+            numLabels = LSVM.instanceSet.getNumLabels;
+            uniqueLabels = unique(LSVM.instanceSet.getLabels);
+            for i=1:numLabels
+                currentLabel = uniqueLabels(i);
+                labels = zeros(LSVM.instanceSet.getNumInstances,1)-1;
+                labels(LSVM.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+                LSVM.models{i} = svmtrain(labels, [(1:size(LSVM.Ktrain,1))', ...
+                    LSVM.Ktrain+eye(size(LSVM.Ktrain,1))*realmin], ...
+                    sprintf(' -t 4 -c %f -b 1 -q', LSVM.cost));
+            end
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(LSVM)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(LSVM.models);
+            [numinstance, ~] = size(LSVM.Ktest);
+            scores = zeros(numModels,numinstance);
+            for i=1:numModels
+                %predict using the stored models
+                tic
+                [~, ~, t] = svmpredict(eye(numinstance,1),...
+                    [(1:numinstance)', LSVM.Ktest], LSVM.models{i},'-b 1 -q');
+                LSVM.predictTotalTime = LSVM.predictTotalTime + toc;
+                LSVM.predictCount = LSVM.predictCount + numinstance;
+                %svmpredict(labels(~idx), [(1:sum(~idx))', K(~idx,idx)], model);
+                %store probability for each class
+                scores(i,:) = t(:,1);
+            end
+            output = zeros(numinstance,1);
+            probabilities = zeros(numinstance,1);
+            %we need these for ranking metrics (e.g. mAP)
+            ranking = scores;
+            for i=1:numinstance
+                %select the class with the highest probability
+                [prob, idx] = max(scores(:,i));
+                uniqueLabels = unique(LSVM.instanceSet.getLabels);
+                %output the label with highest probability
+                output(i,1) = uniqueLabels(idx);
+                %return the probability for the output label
+                probabilities(i,1) = prob;
+            end
+        end
+        
+        function LSVM = reset(LSVM)
+            %delete all stored models
+            LSVM.models = {};
+        end
+        
+        function configInfo = getConfigInfo(LSVM)
+            switch LSVM.kernel
+                case {'linear','spearman','correlation','cosine'}
+                    configInfo = sprintf('LIBSVMFast\tkernel:%s\tcost:%d', LSVM.kernel, LSVM.cost);
+                case 'xcorr'
+                    configInfo = sprintf('LIBSVMFast\tkernel:%s\tcost:%d\tgamma:%d\tmaxlag:%d\tscaleopt:%s', LSVM.kernel, LSVM.cost, LSVM.maxlag,LSVM.scaleopt);
+                otherwise
+                    configInfo = sprintf('LIBSVMFast\tkernel:%s\tcost:%d\tgamma:%d', LSVM.kernel, LSVM.cost, LSVM.gamma);
+%                 otherwise 
+%                     configInfo = 'Error in configuration (only linear and rbf kernels supported for now)';
+            end
+        end
+        
+        function time = getTime(LSVM)
+            time = LSVM.predictTotalTime/LSVM.predictCount;
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.dot b/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.dot
new file mode 100644
index 0000000..d41268e
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  LIBSVMFast -> LIBSVMFast;
+
+  LIBSVMFast [URL="LIBSVMFast.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.html b/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.html
new file mode 100644
index 0000000..804d0a1
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@LIBSVMFast</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@LIBSVMFast">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@LIBSVMFast">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVMFast&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@LIBSVMFast</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@LIBSVMFast" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="LIBSVMFast.html" title="LIBSVMFast" alt="" coords="163,29,159,22,148,15,130,10,108,7,84,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,84,53,108,52,130,49,148,43,159,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.map b/doc/+eegtoolkit/+classification/@LIBSVMFast/graph.map
new file mode 100644
index 0000000..e20b900
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diff --git a/doc/+eegtoolkit/+classification/@LIBSVMFast/index.html b/doc/+eegtoolkit/+classification/@LIBSVMFast/index.html
new file mode 100644
index 0000000..93f80fc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@LIBSVMFast/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@LIBSVMFast</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@LIBSVMFast">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@LIBSVMFast">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVMFast&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@LIBSVMFast</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="LIBSVMFast.html">LIBSVMFast</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLDA/MLDA.html b/doc/+eegtoolkit/+classification/@MLDA/MLDA.html
new file mode 100644
index 0000000..5365bc8
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLDA/MLDA.html
@@ -0,0 +1,183 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MLDA</title>
+  <meta name="keywords" content="MLDA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MLDA</a> &gt; MLDA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MLDA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLDA.html" class="code" title="">MLDA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLDA.html" class="code" title="">MLDA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function MLDA = MLDA(instanceSet, discrimType, delta, gamma, fillCoeffs, scoreTransform,prior)</a></li><li><a href="#_sub2" class="code">function MLDA = build(MLDA)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(MLDA,instance)</a></li><li><a href="#_sub4" class="code">function MLDA = reset(MLDA)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(MLDA)</a></li><li><a href="#_sub6" class="code">function time = getTime(MLDA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MLDA.m">MLDA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MLDA.html" class="code" title="">MLDA</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008        DiscrimType; <span class="comment">% 'linear' (default) | 'quadratic' | 'diagLinear' | 'diagQuadratic' | 'pseudoLinear' | 'pseudoQuadratic'</span>
+0009        Delta <span class="comment">% 0 (default) | nonnegative scalar value that acts as a linear coefficient threshold. Delta must be 0 for quadratic discriminant models.</span>
+0010        Gamma <span class="comment">% scalar value in the range [0,1]. Parameter for regularizing the correlation matrix of predictors.</span>
+0011        FillCoeffs <span class="comment">% on (default) Coeffs property flag, specified as the comma-separated pair consisting of 'FillCoeffs' and 'on' or 'off</span>
+0012        ScoreTransform <span class="comment">% 'none' (default). Score transform function. Check http://www.mathworks.com/help/stats/fitcdiscr.html</span>
+0013        Prior <span class="comment">% 'empirical' (default) or 'uniform'.  Prior probabilities for each class.</span>
+0014        models;
+0015        totalTime;
+0016        totalCount;
+0017     <span class="keyword">end</span>
+0018     
+0019     methods (Access = public)
+0020         <a name="_sub0" href="#_subfunctions" class="code">function MLDA = MLDA(instanceSet, discrimType, delta, gamma, fillCoeffs, scoreTransform,prior)</a>
+0021             <span class="comment">%set default parameters</span>
+0022             <span class="keyword">if</span> nargin &gt; 0
+0023                 MLDA.instanceSet = instanceSet;
+0024             <span class="keyword">end</span>
+0025             <span class="keyword">if</span> nargin &gt; 1
+0026                 MLDA.DiscrimType = discrimType;
+0027             <span class="keyword">end</span>
+0028             <span class="keyword">if</span> nargin &gt; 2 
+0029                 MLDA.Delta=delta;
+0030             <span class="keyword">end</span>
+0031             <span class="keyword">if</span> nargin &gt; 3
+0032                 MLDA.Gamma = gamma;
+0033             <span class="keyword">end</span>
+0034             <span class="keyword">if</span> nargin &gt; 4
+0035                 MLDA.FillCoeffs = fillCoeffs;
+0036             <span class="keyword">end</span>
+0037             <span class="keyword">if</span> nargin &gt; 5
+0038                 MLDA.ScoreTransform = scoreTransform;
+0039             <span class="keyword">end</span>
+0040             <span class="keyword">if</span> nargin &gt; 6
+0041                 MLDA.Prior = prior;
+0042             <span class="keyword">end</span>
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub1" href="#_subfunctions" class="code">function MLDA = build(MLDA)</a>
+0046             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0047             MLDA.reset;
+0048             numLabels = MLDA.instanceSet.getNumLabels;
+0049             uniqueLabels = unique(MLDA.instanceSet.getLabels);
+0050            
+0051             <span class="comment">% ---- Multi-Class ----- %</span>
+0052             instances=MLDA.instanceSet.instances;
+0053             labels=MLDA.instanceSet.labels;
+0054             
+0055             <span class="comment">%LDA.models{1}=fitcecoc(instances,labels,'Coding','ternarycomplete');</span>
+0056             MLDA.models{1} = fitcdiscr(instances,labels,<span class="string">'DiscrimType'</span>,MLDA.DiscrimType,<span class="string">'Delta'</span>,MLDA.Delta,<span class="string">'Gamma'</span>,MLDA.Gamma,<span class="string">'FillCoeffs'</span>,MLDA.FillCoeffs,<span class="string">'ScoreTransform'</span>,MLDA.ScoreTransform, <span class="string">'Prior'</span>,MLDA.Prior);
+0057             
+0058             <span class="comment">% ---- One (vs) All ----- %</span>
+0059 <span class="comment">%             for i=1:numLabels</span>
+0060 <span class="comment">%                 currentLabel = uniqueLabels(i);</span>
+0061 <span class="comment">%                 labels = zeros(LDA.instanceSet.getNumInstances,1)-1;</span>
+0062 <span class="comment">%                 labels(LDA.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;</span>
+0063 <span class="comment">%                 instances = sparse(LDA.instanceSet.getInstances);</span>
+0064 <span class="comment">%                 LDA.models{i} = libsvmtrain(labels,instances, '-t 0 -c 1 -b 1');</span>
+0065 <span class="comment">%                 if LDA.kernel == LDA.KERNEL_LINEAR;</span>
+0066 <span class="comment">%                    %store the models in an instance variable</span>
+0067 <span class="comment">%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -b 1 -q', LDA.kernel, LDA.cost));</span>
+0068 <span class="comment">%                 elseif LDA.kernel == LDA.KERNEL_RBF;</span>
+0069 <span class="comment">%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -g %f -b 1 -q', LDA.kernel, LDA.cost, LDA.gamma));</span>
+0070 <span class="comment">%                 else</span>
+0071 <span class="comment">%                    error('invalid kernel parameter');</span>
+0072 <span class="comment">%                 end</span>
+0073 <span class="comment">%             end</span>
+0074         <span class="keyword">end</span>
+0075         
+0076         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(MLDA,instance)</a>
+0077             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0078             <span class="comment">%output = predicted class</span>
+0079             <span class="comment">%probabilities = probability for predicted class</span>
+0080             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0081             
+0082             
+0083             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0084             numModels = length(MLDA.models);
+0085             [numinstance, ~] = size(instance);
+0086             scores = zeros(numModels,numinstance);
+0087              
+0088             <span class="comment">% ---- Multi-class ----- %</span>
+0089             tic
+0090             [label,scores,cost] = predict(MLDA.models{1},instance); 
+0091             MLDA.totalTime = MLDA.totalTime + toc;
+0092             MLDA.totalCount = MLDA.totalCount  + numinstance;
+0093             <span class="comment">% ---- One (vs) All -----%</span>
+0094 <span class="comment">%              for i=1:numModels</span>
+0095 <span class="comment">%                  %predict using the stored models</span>
+0096 <span class="comment">%                  [label,score,cost] = predict(LDA.models{i},instance);</span>
+0097 <span class="comment">%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');</span>
+0098 <span class="comment">%                 %store probability for each class</span>
+0099 <span class="comment">%                 scores(i,:) = score(:,1);</span>
+0100 <span class="comment">%             end</span>
+0101 
+0102              output = zeros(numinstance,1);
+0103              probabilities = zeros(numinstance,1);
+0104              <span class="comment">%we need these for ranking metrics (e.g. mAP)</span>
+0105              ranking = scores;
+0106              <span class="keyword">for</span> i=1:numinstance
+0107                  <span class="comment">%select the class with the highest probability</span>
+0108                  [prob, idx] = max(scores(i,:));
+0109                  uniqueLabels = unique(MLDA.instanceSet.getLabels);
+0110                  <span class="comment">%output the label with highest probability</span>
+0111                  output(i,1) = uniqueLabels(idx);
+0112                  <span class="comment">%return the probability for the output label</span>
+0113                  probabilities(i,1) = prob;
+0114              <span class="keyword">end</span>
+0115         <span class="keyword">end</span>
+0116         
+0117         <a name="_sub3" href="#_subfunctions" class="code">function MLDA = reset(MLDA)</a>
+0118             <span class="comment">%delete all stored models</span>
+0119             MLDA.models = {};
+0120         <span class="keyword">end</span>
+0121         
+0122         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(MLDA)</a>
+0123             configInfo = sprintf(<span class="string">'MLDA\tdiscrimtype:%s\tdelta:%f\tgamma:%f\tfillcoeffs:%d\tscoretransform:%s\tprior:%s'</span>,MLDA.DiscrimType, MLDA.Delta, MLDA.Gamma, MLDA.FillCoeffs, MLDA.ScoreTransform, MLDA.Prior);
+0124         <span class="keyword">end</span>
+0125         
+0126                         
+0127         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MLDA)</a>
+0128             time = MLDA.totalTime/MLDA.totalCount;
+0129         <span class="keyword">end</span>
+0130                 
+0131     <span class="keyword">end</span>
+0132 <span class="keyword">end</span>
+0133</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLDA/MLDA.m b/doc/+eegtoolkit/+classification/@MLDA/MLDA.m
new file mode 100644
index 0000000..92261f4
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLDA/MLDA.m
@@ -0,0 +1,133 @@
+classdef MLDA < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties
+       DiscrimType; % 'linear' (default) | 'quadratic' | 'diagLinear' | 'diagQuadratic' | 'pseudoLinear' | 'pseudoQuadratic'
+       Delta % 0 (default) | nonnegative scalar value that acts as a linear coefficient threshold. Delta must be 0 for quadratic discriminant models. 
+       Gamma % scalar value in the range [0,1]. Parameter for regularizing the correlation matrix of predictors.
+       FillCoeffs % on (default) Coeffs property flag, specified as the comma-separated pair consisting of 'FillCoeffs' and 'on' or 'off
+       ScoreTransform % 'none' (default). Score transform function. Check http://www.mathworks.com/help/stats/fitcdiscr.html
+       Prior % 'empirical' (default) or 'uniform'.  Prior probabilities for each class. 
+       models;
+       totalTime;
+       totalCount;
+    end
+    
+    methods (Access = public)
+        function MLDA = MLDA(instanceSet, discrimType, delta, gamma, fillCoeffs, scoreTransform,prior)
+            %set default parameters
+            if nargin > 0
+                MLDA.instanceSet = instanceSet;
+            end
+            if nargin > 1
+                MLDA.DiscrimType = discrimType;
+            end
+            if nargin > 2 
+                MLDA.Delta=delta;
+            end
+            if nargin > 3
+                MLDA.Gamma = gamma;
+            end
+            if nargin > 4
+                MLDA.FillCoeffs = fillCoeffs;
+            end
+            if nargin > 5
+                MLDA.ScoreTransform = scoreTransform;
+            end
+            if nargin > 6
+                MLDA.Prior = prior;
+            end
+        end
+        
+        function MLDA = build(MLDA)
+            %clear all from previous calls to "build"
+            MLDA.reset;
+            numLabels = MLDA.instanceSet.getNumLabels;
+            uniqueLabels = unique(MLDA.instanceSet.getLabels);
+           
+            % ---- Multi-Class ----- %
+            instances=MLDA.instanceSet.instances;
+            labels=MLDA.instanceSet.labels;
+            
+            %LDA.models{1}=fitcecoc(instances,labels,'Coding','ternarycomplete');
+            MLDA.models{1} = fitcdiscr(instances,labels,'DiscrimType',MLDA.DiscrimType,'Delta',MLDA.Delta,'Gamma',MLDA.Gamma,'FillCoeffs',MLDA.FillCoeffs,'ScoreTransform',MLDA.ScoreTransform, 'Prior',MLDA.Prior);
+            
+            % ---- One (vs) All ----- %
+%             for i=1:numLabels
+%                 currentLabel = uniqueLabels(i);
+%                 labels = zeros(LDA.instanceSet.getNumInstances,1)-1;
+%                 labels(LDA.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+%                 instances = sparse(LDA.instanceSet.getInstances);
+%                 LDA.models{i} = libsvmtrain(labels,instances, '-t 0 -c 1 -b 1');
+%                 if LDA.kernel == LDA.KERNEL_LINEAR;
+%                    %store the models in an instance variable
+%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -b 1 -q', LDA.kernel, LDA.cost));
+%                 elseif LDA.kernel == LDA.KERNEL_RBF;
+%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -g %f -b 1 -q', LDA.kernel, LDA.cost, LDA.gamma));
+%                 else
+%                    error('invalid kernel parameter');
+%                 end
+%             end
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(MLDA,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(MLDA.models);
+            [numinstance, ~] = size(instance);
+            scores = zeros(numModels,numinstance);
+             
+            % ---- Multi-class ----- %
+            tic
+            [label,scores,cost] = predict(MLDA.models{1},instance); 
+            MLDA.totalTime = MLDA.totalTime + toc;
+            MLDA.totalCount = MLDA.totalCount  + numinstance;
+            % ---- One (vs) All -----%
+%              for i=1:numModels
+%                  %predict using the stored models
+%                  [label,score,cost] = predict(LDA.models{i},instance);
+%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = score(:,1);
+%             end
+
+             output = zeros(numinstance,1);
+             probabilities = zeros(numinstance,1);
+             %we need these for ranking metrics (e.g. mAP)
+             ranking = scores;
+             for i=1:numinstance
+                 %select the class with the highest probability
+                 [prob, idx] = max(scores(i,:));
+                 uniqueLabels = unique(MLDA.instanceSet.getLabels);
+                 %output the label with highest probability
+                 output(i,1) = uniqueLabels(idx);
+                 %return the probability for the output label
+                 probabilities(i,1) = prob;
+             end
+        end
+        
+        function MLDA = reset(MLDA)
+            %delete all stored models
+            MLDA.models = {};
+        end
+        
+        function configInfo = getConfigInfo(MLDA)
+            configInfo = sprintf('MLDA\tdiscrimtype:%s\tdelta:%f\tgamma:%f\tfillcoeffs:%d\tscoretransform:%s\tprior:%s',MLDA.DiscrimType, MLDA.Delta, MLDA.Gamma, MLDA.FillCoeffs, MLDA.ScoreTransform, MLDA.Prior);
+        end
+        
+                        
+        function time = getTime(MLDA)
+            time = MLDA.totalTime/MLDA.totalCount;
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@MLDA/graph.dot b/doc/+eegtoolkit/+classification/@MLDA/graph.dot
new file mode 100644
index 0000000..4680b13
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLDA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MLDA -> MLDA;
+
+  MLDA [URL="MLDA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLDA/graph.html b/doc/+eegtoolkit/+classification/@MLDA/graph.html
new file mode 100644
index 0000000..90ac050
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLDA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@MLDA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@MLDA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLDA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLDA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MLDA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MLDA.html" title="MLDA" alt="" coords="104,29,102,22,95,15,84,10,70,7,55,5,39,7,26,10,15,15,8,22,5,29,8,37,15,43,26,49,39,52,55,53,70,52,84,49,95,43,102,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLDA/graph.map b/doc/+eegtoolkit/+classification/@MLDA/graph.map
new file mode 100644
index 0000000..42801a4
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLDA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="MLDA.html" title="MLDA" alt="" coords="104,29,102,22,95,15,84,10,70,7,55,5,39,7,26,10,15,15,8,22,5,29,8,37,15,43,26,49,39,52,55,53,70,52,84,49,95,43,102,37">
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diff --git a/doc/+eegtoolkit/+classification/@MLDA/index.html b/doc/+eegtoolkit/+classification/@MLDA/index.html
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+  <title>Index for Directory ./+eegtoolkit/+classification/@MLDA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@MLDA">
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+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@MLDA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MLDA.html">MLDA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
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diff --git a/doc/+eegtoolkit/+classification/@MLR/MLR.html b/doc/+eegtoolkit/+classification/@MLR/MLR.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MLR</title>
+  <meta name="keywords" content="MLR">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MLR</a> &gt; MLR.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MLR
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLR.html" class="code" title="">MLR</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLR.html" class="code" title="">MLR</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function MLR = MLR(instanceSet)</a></li><li><a href="#_sub2" class="code">function MLR = build(MLR)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(MLR,instance)</a></li><li><a href="#_sub4" class="code">function MLR = reset(MLR)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(MLR)</a></li><li><a href="#_sub6" class="code">function time = getTime(MLR)</a></li><li><a href="#_sub7" class="code">function Proj_W=pca_func(MLR,data)</a></li><li><a href="#_sub8" class="code">function W_mlr=MultiLR(MLR,train_Feat,train_Y)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MLR.m">MLR.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MLR.html" class="code" title="">MLR</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004         
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008         W_mlr;
+0009         PCA_mat;
+0010         trainFeat;
+0011     <span class="keyword">end</span>
+0012     
+0013     methods (Access = public)
+0014         <a name="_sub0" href="#_subfunctions" class="code">function MLR = MLR(instanceSet)</a>
+0015             <span class="keyword">if</span> nargin &gt; 0
+0016                 MLR.instanceSet = instanceSet;
+0017             <span class="keyword">end</span>
+0018             
+0019         <span class="keyword">end</span>
+0020         
+0021         <a name="_sub1" href="#_subfunctions" class="code">function MLR = build(MLR)</a>
+0022             MLR.reset();
+0023             data = MLR.instanceSet.getInstances;
+0024             data = data';
+0025             labels = MLR.instanceSet.getLabels;
+0026             numTrials = length(labels);
+0027             train_Y = zeros(length(unique(labels)),numTrials);
+0028             <span class="keyword">for</span> i = 1 : numTrials
+0029                 train_Y(labels(i),i) = 1;
+0030             <span class="keyword">end</span>
+0031             [Ydim,Num]=size(train_Y);
+0032             PCA_W=MLR.pca_func(data);
+0033             train_Data=PCA_W'*data;
+0034             train_Data=[ones(1,numTrials);train_Data];
+0035             MLR.W_mlr = MLR.MultiLR(train_Data,train_Y);<span class="comment">%inv(train_Data*train_Data')*train_Data*train_Y';%(train_Data'*train_Data)\train_Data'*train_Y;%MultiLR(train_Data,train_Y);</span>
+0036             MLR.PCA_mat=PCA_W;
+0037             mtrainFeat=MLR.W_mlr'*train_Data;
+0038             MLR.trainFeat=mtrainFeat;
+0039         <span class="keyword">end</span>
+0040         
+0041         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(MLR,instance)</a>
+0042             
+0043             N = size(instance,1);
+0044             instance = instance';
+0045             test_Data=MLR.PCA_mat'*instance;
+0046             test_Data=[ones(1,N);test_Data];
+0047             testFeat=MLR.W_mlr'*test_Data;
+0048             output=knnclassify(testFeat',MLR.trainFeat',MLR.instanceSet.getLabels,5,<span class="string">'euclidean'</span>);
+0049             probabilities=zeros(N,1);
+0050             ranking=zeros(N,1);
+0051             
+0052         <span class="keyword">end</span>
+0053         
+0054         <a name="_sub3" href="#_subfunctions" class="code">function MLR = reset(MLR)</a>
+0055             <span class="comment">%delete all stored models</span>
+0056             MLR.W_mlr=[];
+0057             MLR.PCA_mat=[];
+0058             MLR.trainFeat=[];
+0059         <span class="keyword">end</span>
+0060         
+0061         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(MLR)</a>
+0062             configInfo = sprintf(<span class="string">'MLR'</span>);
+0063         <span class="keyword">end</span>
+0064         
+0065         
+0066         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MLR)</a>
+0067             time = 0;
+0068         <span class="keyword">end</span>
+0069         
+0070     <span class="keyword">end</span>
+0071     
+0072     methods (Access = private)
+0073         <a name="_sub6" href="#_subfunctions" class="code">function Proj_W=pca_func(MLR,data)</a>
+0074             Proj_W=[];
+0075             meanData=mean(data,2);
+0076             data=data-repmat(meanData,1,size(data,2));
+0077             <span class="comment">% stdVar=std(data')';</span>
+0078             <span class="comment">% staData=(data-repmat(meanData,1,size(data,2)))./repmat(stdVar,1,size(data,2));</span>
+0079             <span class="comment">% data=staData;</span>
+0080             [V,S]=eig(data'*data);
+0081             [sorted_diagS,sorted_rank]=sort(diag(S),<span class="string">'descend'</span>);
+0082             sorted_S=diag(sorted_diagS);
+0083             V=V(:,sorted_rank);
+0084             r=rank(sorted_S);
+0085             S1=sorted_S(1:r,1:r);
+0086             V1=V(:,1:r);
+0087             U=data*V1*S1^(-0.5);
+0088             <span class="comment">%[sorted_S,sorted_rank]=sort(diag(S),'descend');</span>
+0089             All_energy=sum(diag(S1));
+0090             sorted_energy=diag(S1);
+0091             <span class="keyword">for</span> j=1:r
+0092                 <span class="keyword">if</span> (sum(sorted_energy(1:j))/All_energy)&gt;0.99
+0093                     <span class="keyword">break</span>
+0094                 <span class="keyword">end</span>
+0095             <span class="keyword">end</span>
+0096             Proj_W=U(:,1:j);
+0097         <span class="keyword">end</span>
+0098         <a name="_sub7" href="#_subfunctions" class="code">function W_mlr=MultiLR(MLR,train_Feat,train_Y)</a>
+0099             
+0100             <span class="comment">% Multiple linear regression</span>
+0101             <span class="comment">% train_Feat: training samples</span>
+0102             <span class="comment">% train_Y: label matrix</span>
+0103             
+0104             [U,Sigma,V]=svd(train_Feat,<span class="string">'econ'</span>);
+0105             r=rank(Sigma);
+0106             U1=U(:,1:r);
+0107             V1=V(:,1:r);
+0108             Sigma_r=diag(Sigma(1:r, 1:r));
+0109             W_mlr=U1*diag(1./Sigma_r)*V1'*train_Y';
+0110             
+0111             
+0112         <span class="keyword">end</span>
+0113     <span class="keyword">end</span>
+0114 <span class="keyword">end</span>
+0115</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLR/MLR.m b/doc/+eegtoolkit/+classification/@MLR/MLR.m
new file mode 100644
index 0000000..a9eb9b5
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLR/MLR.m
@@ -0,0 +1,115 @@
+classdef MLR < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+        
+    end
+    
+    properties
+        W_mlr;
+        PCA_mat;
+        trainFeat;
+    end
+    
+    methods (Access = public)
+        function MLR = MLR(instanceSet)
+            if nargin > 0
+                MLR.instanceSet = instanceSet;
+            end
+            
+        end
+        
+        function MLR = build(MLR)
+            MLR.reset();
+            data = MLR.instanceSet.getInstances;
+            data = data';
+            labels = MLR.instanceSet.getLabels;
+            numTrials = length(labels);
+            train_Y = zeros(length(unique(labels)),numTrials);
+            for i = 1 : numTrials
+                train_Y(labels(i),i) = 1;
+            end
+            [Ydim,Num]=size(train_Y);
+            PCA_W=MLR.pca_func(data);
+            train_Data=PCA_W'*data;
+            train_Data=[ones(1,numTrials);train_Data];
+            MLR.W_mlr = MLR.MultiLR(train_Data,train_Y);%inv(train_Data*train_Data')*train_Data*train_Y';%(train_Data'*train_Data)\train_Data'*train_Y;%MultiLR(train_Data,train_Y);
+            MLR.PCA_mat=PCA_W;
+            mtrainFeat=MLR.W_mlr'*train_Data;
+            MLR.trainFeat=mtrainFeat;
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(MLR,instance)
+            
+            N = size(instance,1);
+            instance = instance';
+            test_Data=MLR.PCA_mat'*instance;
+            test_Data=[ones(1,N);test_Data];
+            testFeat=MLR.W_mlr'*test_Data;
+            output=knnclassify(testFeat',MLR.trainFeat',MLR.instanceSet.getLabels,5,'euclidean');
+            probabilities=zeros(N,1);
+            ranking=zeros(N,1);
+            
+        end
+        
+        function MLR = reset(MLR)
+            %delete all stored models
+            MLR.W_mlr=[];
+            MLR.PCA_mat=[];
+            MLR.trainFeat=[];
+        end
+        
+        function configInfo = getConfigInfo(MLR)
+            configInfo = sprintf('MLR');
+        end
+        
+        
+        function time = getTime(MLR)
+            time = 0;
+        end
+        
+    end
+    
+    methods (Access = private)
+        function Proj_W=pca_func(MLR,data)
+            Proj_W=[];
+            meanData=mean(data,2);
+            data=data-repmat(meanData,1,size(data,2));
+            % stdVar=std(data')';
+            % staData=(data-repmat(meanData,1,size(data,2)))./repmat(stdVar,1,size(data,2));
+            % data=staData;
+            [V,S]=eig(data'*data);
+            [sorted_diagS,sorted_rank]=sort(diag(S),'descend');
+            sorted_S=diag(sorted_diagS);
+            V=V(:,sorted_rank);
+            r=rank(sorted_S);
+            S1=sorted_S(1:r,1:r);
+            V1=V(:,1:r);
+            U=data*V1*S1^(-0.5);
+            %[sorted_S,sorted_rank]=sort(diag(S),'descend');
+            All_energy=sum(diag(S1));
+            sorted_energy=diag(S1);
+            for j=1:r
+                if (sum(sorted_energy(1:j))/All_energy)>0.99
+                    break
+                end
+            end
+            Proj_W=U(:,1:j);
+        end
+        function W_mlr=MultiLR(MLR,train_Feat,train_Y)
+            
+            % Multiple linear regression
+            % train_Feat: training samples
+            % train_Y: label matrix
+            
+            [U,Sigma,V]=svd(train_Feat,'econ');
+            r=rank(Sigma);
+            U1=U(:,1:r);
+            V1=V(:,1:r);
+            Sigma_r=diag(Sigma(1:r, 1:r));
+            W_mlr=U1*diag(1./Sigma_r)*V1'*train_Y';
+            
+            
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@MLR/graph.dot b/doc/+eegtoolkit/+classification/@MLR/graph.dot
new file mode 100644
index 0000000..a73f6b1
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLR/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MLR -> MLR;
+
+  MLR [URL="MLR.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLR/graph.html b/doc/+eegtoolkit/+classification/@MLR/graph.html
new file mode 100644
index 0000000..2412fbb
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLR/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@MLR</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@MLR">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLR</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MLR" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MLR.html" title="MLR" alt="" coords="86,29,84,22,78,15,69,10,58,7,45,5,33,7,21,10,12,15,7,22,5,29,7,37,12,43,21,49,33,52,45,53,58,52,69,49,78,43,84,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLR/graph.map b/doc/+eegtoolkit/+classification/@MLR/graph.map
new file mode 100644
index 0000000..68a65dc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLR/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="MLR.html" title="MLR" alt="" coords="86,29,84,22,78,15,69,10,58,7,45,5,33,7,21,10,12,15,7,22,5,29,7,37,12,43,21,49,33,52,45,53,58,52,69,49,78,43,84,37">
diff --git a/doc/+eegtoolkit/+classification/@MLR/graph.png b/doc/+eegtoolkit/+classification/@MLR/graph.png
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diff --git a/doc/+eegtoolkit/+classification/@MLR/index.html b/doc/+eegtoolkit/+classification/@MLR/index.html
new file mode 100644
index 0000000..fe6fcbe
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLR/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@MLR</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@MLR">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@MLR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@MLR</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MLR.html">MLR</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.html b/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.html
new file mode 100644
index 0000000..2018789
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.html
@@ -0,0 +1,190 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MLTREE</title>
+  <meta name="keywords" content="MLTREE">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MLTREE</a> &gt; MLTREE.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTREE&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MLTREE
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLTREE.html" class="code" title="">MLTREE</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLTREE.html" class="code" title="">MLTREE</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function MLTREE = MLTREE(instanceSet, algorithmForCategorical, maxNumSplits, minLeafSize, minParentSize, numVariablesToSample, scoreTransform, prior)</a></li><li><a href="#_sub2" class="code">function MLTREE = build(MLTREE)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(MLTREE,instance)</a></li><li><a href="#_sub4" class="code">function MLTREE = reset(MLTREE)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(MLTREE)</a></li><li><a href="#_sub6" class="code">function time = getTime(MLTREE)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MLTREE.m">MLTREE.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MLTREE.html" class="code" title="">MLTREE</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008        AlgorithmForCategorical; <span class="comment">% Algorithm for best categorical predictor split 'Exact' | 'PullLeft' | 'PCA' | 'OVAbyClass'</span>
+0009        MaxNumSplits; <span class="comment">% Maximal number of decision splits. size(X,1) - 1 (default) | positive integer</span>
+0010        MinLeafSize; <span class="comment">% Minimum number of leaf node observations 1 (default) | positive integer value</span>
+0011        MinParentSize; <span class="comment">% Minimum number of branch node observations 10 (default) | positive integer value</span>
+0012        NumVariablesToSample; <span class="comment">% Number of predictors to select at random for each split 'all' | positive integer value</span>
+0013        ScoreTransform <span class="comment">% 'none' (default). Score transform function. Check http://www.mathworks.com/help/stats/fitcdiscr.html</span>
+0014        Prior; <span class="comment">% Prior probabilities 'empirical' (default) | 'uniform' | vector of scalar values | structure</span>
+0015        models;
+0016        totalTime;
+0017        totalCount;
+0018     <span class="keyword">end</span>
+0019     
+0020     methods (Access = public)
+0021         <a name="_sub0" href="#_subfunctions" class="code">function MLTREE = MLTREE(instanceSet, algorithmForCategorical, maxNumSplits, minLeafSize, minParentSize, numVariablesToSample, scoreTransform, prior)</a>
+0022             <span class="comment">%set default parameters</span>
+0023             <span class="keyword">if</span> nargin &gt; 0
+0024                 MLTREE.instanceSet = instanceSet;
+0025             <span class="keyword">end</span>
+0026             <span class="keyword">if</span> nargin &gt; 1
+0027                 MLTREE.AlgorithmForCategorical = algorithmForCategorical;
+0028             <span class="keyword">end</span>
+0029             <span class="keyword">if</span> nargin &gt; 2 
+0030                 MLTREE.MaxNumSplits=maxNumSplits;
+0031             <span class="keyword">end</span>
+0032             <span class="keyword">if</span> nargin &gt; 3
+0033                 MLTREE.MinLeafSize = minLeafSize;
+0034             <span class="keyword">end</span>
+0035             <span class="keyword">if</span> nargin &gt; 4
+0036                 MLTREE.MinParentSize = minParentSize;
+0037             <span class="keyword">end</span>
+0038             <span class="keyword">if</span> nargin &gt; 5
+0039                 MLTREE.NumVariablesToSample = numVariablesToSample;
+0040             <span class="keyword">end</span>
+0041             <span class="keyword">if</span> nargin &gt; 6
+0042                 MLTREE.ScoreTransform = scoreTransform;
+0043             <span class="keyword">end</span>
+0044             <span class="keyword">if</span> nargin &gt; 7
+0045                 MLTREE.Prior = prior;
+0046             <span class="keyword">end</span>
+0047             MLTREE.totalTime = 0;
+0048             MLTREE.totalCount = 0;
+0049         <span class="keyword">end</span>
+0050         
+0051         <a name="_sub1" href="#_subfunctions" class="code">function MLTREE = build(MLTREE)</a>
+0052             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0053             MLTREE.reset;
+0054             numLabels = MLTREE.instanceSet.getNumLabels;
+0055             uniqueLabels = unique(MLTREE.instanceSet.getLabels);
+0056            
+0057             <span class="comment">% ---- Multi-Class ----- %</span>
+0058             instances=MLTREE.instanceSet.instances;
+0059             labels=MLTREE.instanceSet.labels;
+0060             
+0061             <span class="comment">%LDA.models{1}=fitcecoc(instances,labels,'Coding','ternarycomplete');</span>
+0062             MLTREE.models{1} = fitctree(instances,labels,<span class="string">'AlgorithmForCategorical'</span>,MLTREE.AlgorithmForCategorical,<span class="string">'MaxNumSplits'</span>,MLTREE.MaxNumSplits,<span class="string">'MinLeafSize'</span>,MLTREE.MinLeafSize,<span class="string">'MinParentSize'</span>,MLTREE.MinParentSize,<span class="string">'NumVariablesToSample'</span>, MLTREE.NumVariablesToSample,<span class="string">'ScoreTransform'</span>,MLTREE.ScoreTransform, <span class="string">'Prior'</span>,MLTREE.Prior);
+0063      
+0064             
+0065             <span class="comment">% ---- One (vs) All ----- %</span>
+0066 <span class="comment">%             for i=1:numLabels</span>
+0067 <span class="comment">%                 currentLabel = uniqueLabels(i);</span>
+0068 <span class="comment">%                 labels = zeros(LDA.instanceSet.getNumInstances,1)-1;</span>
+0069 <span class="comment">%                 labels(LDA.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;</span>
+0070 <span class="comment">%                 instances = sparse(LDA.instanceSet.getInstances);</span>
+0071 <span class="comment">%                 LDA.models{i} = libsvmtrain(labels,instances, '-t 0 -c 1 -b 1');</span>
+0072 <span class="comment">%                 if LDA.kernel == LDA.KERNEL_LINEAR;</span>
+0073 <span class="comment">%                    %store the models in an instance variable</span>
+0074 <span class="comment">%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -b 1 -q', LDA.kernel, LDA.cost));</span>
+0075 <span class="comment">%                 elseif LDA.kernel == LDA.KERNEL_RBF;</span>
+0076 <span class="comment">%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -g %f -b 1 -q', LDA.kernel, LDA.cost, LDA.gamma));</span>
+0077 <span class="comment">%                 else</span>
+0078 <span class="comment">%                    error('invalid kernel parameter');</span>
+0079 <span class="comment">%                 end</span>
+0080 <span class="comment">%             end</span>
+0081         <span class="keyword">end</span>
+0082         
+0083         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(MLTREE,instance)</a>
+0084             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0085             <span class="comment">%output = predicted class</span>
+0086             <span class="comment">%probabilities = probability for predicted class</span>
+0087             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0088             
+0089             
+0090             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0091             numModels = length(MLTREE.models);
+0092             [numinstance, ~] = size(instance);
+0093             scores = zeros(numModels,numinstance);
+0094              
+0095             <span class="comment">% ---- Multi-class ----- %</span>
+0096             tic
+0097             [label,scores,cost] = predict(MLTREE.models{1},instance); 
+0098             MLTREE.totalTime = MLTREE.totalTime + toc;
+0099             MLTREE.totalCount = MLTREE.totalCount + numinstance;
+0100             <span class="comment">% ---- One (vs) All -----%</span>
+0101 <span class="comment">%              for i=1:numModels</span>
+0102 <span class="comment">%                  %predict using the stored models</span>
+0103 <span class="comment">%                  [label,score,cost] = predict(LDA.models{i},instance);</span>
+0104 <span class="comment">%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');</span>
+0105 <span class="comment">%                 %store probability for each class</span>
+0106 <span class="comment">%                 scores(i,:) = score(:,1);</span>
+0107 <span class="comment">%             end</span>
+0108 
+0109              output = zeros(numinstance,1);
+0110              probabilities = zeros(numinstance,1);
+0111              <span class="comment">%we need these for ranking metrics (e.g. mAP)</span>
+0112              ranking = scores;
+0113              <span class="keyword">for</span> i=1:numinstance
+0114                  <span class="comment">%select the class with the highest probability</span>
+0115                  [prob, idx] = max(scores(i,:));
+0116                  uniqueLabels = unique(MLTREE.instanceSet.getLabels);
+0117                  <span class="comment">%output the label with highest probability</span>
+0118                  output(i,1) = uniqueLabels(idx);
+0119                  <span class="comment">%return the probability for the output label</span>
+0120                  probabilities(i,1) = prob;
+0121              <span class="keyword">end</span>
+0122         <span class="keyword">end</span>
+0123         
+0124         <a name="_sub3" href="#_subfunctions" class="code">function MLTREE = reset(MLTREE)</a>
+0125             <span class="comment">%delete all stored models</span>
+0126             MLTREE.models = {};
+0127         <span class="keyword">end</span>
+0128         
+0129         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(MLTREE)</a>
+0130             configInfo = <span class="string">'MLTREE (Config info not supported yet)'</span>;
+0131         <span class="keyword">end</span>
+0132         
+0133                         
+0134         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MLTREE)</a>
+0135             time = MLTREE.totalTime/MLTREE.totalCount;
+0136         <span class="keyword">end</span>
+0137                 
+0138     <span class="keyword">end</span>
+0139 <span class="keyword">end</span>
+0140</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.m b/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.m
new file mode 100644
index 0000000..e1cd769
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.m
@@ -0,0 +1,140 @@
+classdef MLTREE < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties
+       AlgorithmForCategorical; % Algorithm for best categorical predictor split 'Exact' | 'PullLeft' | 'PCA' | 'OVAbyClass' 
+       MaxNumSplits; % Maximal number of decision splits. size(X,1) - 1 (default) | positive integer
+       MinLeafSize; % Minimum number of leaf node observations 1 (default) | positive integer value
+       MinParentSize; % Minimum number of branch node observations 10 (default) | positive integer value
+       NumVariablesToSample; % Number of predictors to select at random for each split 'all' | positive integer value
+       ScoreTransform % 'none' (default). Score transform function. Check http://www.mathworks.com/help/stats/fitcdiscr.html
+       Prior; % Prior probabilities 'empirical' (default) | 'uniform' | vector of scalar values | structure
+       models;
+       totalTime;
+       totalCount;
+    end
+    
+    methods (Access = public)
+        function MLTREE = MLTREE(instanceSet, algorithmForCategorical, maxNumSplits, minLeafSize, minParentSize, numVariablesToSample, scoreTransform, prior)
+            %set default parameters
+            if nargin > 0
+                MLTREE.instanceSet = instanceSet;
+            end
+            if nargin > 1
+                MLTREE.AlgorithmForCategorical = algorithmForCategorical;
+            end
+            if nargin > 2 
+                MLTREE.MaxNumSplits=maxNumSplits;
+            end
+            if nargin > 3
+                MLTREE.MinLeafSize = minLeafSize;
+            end
+            if nargin > 4
+                MLTREE.MinParentSize = minParentSize;
+            end
+            if nargin > 5
+                MLTREE.NumVariablesToSample = numVariablesToSample;
+            end
+            if nargin > 6
+                MLTREE.ScoreTransform = scoreTransform;
+            end
+            if nargin > 7
+                MLTREE.Prior = prior;
+            end
+            MLTREE.totalTime = 0;
+            MLTREE.totalCount = 0;
+        end
+        
+        function MLTREE = build(MLTREE)
+            %clear all from previous calls to "build"
+            MLTREE.reset;
+            numLabels = MLTREE.instanceSet.getNumLabels;
+            uniqueLabels = unique(MLTREE.instanceSet.getLabels);
+           
+            % ---- Multi-Class ----- %
+            instances=MLTREE.instanceSet.instances;
+            labels=MLTREE.instanceSet.labels;
+            
+            %LDA.models{1}=fitcecoc(instances,labels,'Coding','ternarycomplete');
+            MLTREE.models{1} = fitctree(instances,labels,'AlgorithmForCategorical',MLTREE.AlgorithmForCategorical,'MaxNumSplits',MLTREE.MaxNumSplits,'MinLeafSize',MLTREE.MinLeafSize,'MinParentSize',MLTREE.MinParentSize,'NumVariablesToSample', MLTREE.NumVariablesToSample,'ScoreTransform',MLTREE.ScoreTransform, 'Prior',MLTREE.Prior);
+     
+            
+            % ---- One (vs) All ----- %
+%             for i=1:numLabels
+%                 currentLabel = uniqueLabels(i);
+%                 labels = zeros(LDA.instanceSet.getNumInstances,1)-1;
+%                 labels(LDA.instanceSet.getInstanceIndicesForLabel(currentLabel)) = 1;
+%                 instances = sparse(LDA.instanceSet.getInstances);
+%                 LDA.models{i} = libsvmtrain(labels,instances, '-t 0 -c 1 -b 1');
+%                 if LDA.kernel == LDA.KERNEL_LINEAR;
+%                    %store the models in an instance variable
+%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -b 1 -q', LDA.kernel, LDA.cost));
+%                 elseif LDA.kernel == LDA.KERNEL_RBF;
+%                    LDA.models{i} = libsvmtrain(labels, instances, sprintf('-t %d -c %f -g %f -b 1 -q', LDA.kernel, LDA.cost, LDA.gamma));
+%                 else
+%                    error('invalid kernel parameter');
+%                 end
+%             end
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(MLTREE,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(MLTREE.models);
+            [numinstance, ~] = size(instance);
+            scores = zeros(numModels,numinstance);
+             
+            % ---- Multi-class ----- %
+            tic
+            [label,scores,cost] = predict(MLTREE.models{1},instance); 
+            MLTREE.totalTime = MLTREE.totalTime + toc;
+            MLTREE.totalCount = MLTREE.totalCount + numinstance;
+            % ---- One (vs) All -----%
+%              for i=1:numModels
+%                  %predict using the stored models
+%                  [label,score,cost] = predict(LDA.models{i},instance);
+%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = score(:,1);
+%             end
+
+             output = zeros(numinstance,1);
+             probabilities = zeros(numinstance,1);
+             %we need these for ranking metrics (e.g. mAP)
+             ranking = scores;
+             for i=1:numinstance
+                 %select the class with the highest probability
+                 [prob, idx] = max(scores(i,:));
+                 uniqueLabels = unique(MLTREE.instanceSet.getLabels);
+                 %output the label with highest probability
+                 output(i,1) = uniqueLabels(idx);
+                 %return the probability for the output label
+                 probabilities(i,1) = prob;
+             end
+        end
+        
+        function MLTREE = reset(MLTREE)
+            %delete all stored models
+            MLTREE.models = {};
+        end
+        
+        function configInfo = getConfigInfo(MLTREE)
+            configInfo = 'MLTREE (Config info not supported yet)';
+        end
+        
+                        
+        function time = getTime(MLTREE)
+            time = MLTREE.totalTime/MLTREE.totalCount;
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@MLTREE/graph.dot b/doc/+eegtoolkit/+classification/@MLTREE/graph.dot
new file mode 100644
index 0000000..4ad5e85
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTREE/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MLTREE -> MLTREE;
+
+  MLTREE [URL="MLTREE.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTREE/graph.html b/doc/+eegtoolkit/+classification/@MLTREE/graph.html
new file mode 100644
index 0000000..17463a8
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTREE/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@MLTREE</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@MLTREE">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLTREE">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTREE&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLTREE</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MLTREE" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MLTREE.html" title="MLTREE" alt="" coords="128,29,125,22,116,15,103,10,86,7,67,5,48,7,31,10,17,15,8,22,5,29,8,37,17,43,31,49,48,52,67,53,86,52,103,49,116,43,125,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTREE/graph.map b/doc/+eegtoolkit/+classification/@MLTREE/graph.map
new file mode 100644
index 0000000..ff76d66
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTREE/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="MLTREE.html" title="MLTREE" alt="" coords="128,29,125,22,116,15,103,10,86,7,67,5,48,7,31,10,17,15,8,22,5,29,8,37,17,43,31,49,48,52,67,53,86,52,103,49,116,43,125,37">
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diff --git a/doc/+eegtoolkit/+classification/@MLTREE/index.html b/doc/+eegtoolkit/+classification/@MLTREE/index.html
new file mode 100644
index 0000000..8f9c555
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+++ b/doc/+eegtoolkit/+classification/@MLTREE/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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+  <title>Index for Directory ./+eegtoolkit/+classification/@MLTREE</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@MLTREE">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@MLTREE">
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+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTREE&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@MLTREE</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MLTREE.html">MLTREE</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html
new file mode 100644
index 0000000..e824f30
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html
@@ -0,0 +1,154 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MLTboxMulticlass</title>
+  <meta name="keywords" content="MLTboxMulticlass">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MLTboxMulticlass</a> &gt; MLTboxMulticlass.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MLTboxMulticlass
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLTboxMulticlass.html" class="code" title="">MLTboxMulticlass</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLTboxMulticlass.html" class="code" title="">MLTboxMulticlass</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function MLC = MLTboxMulticlass(instanceSet, learners, coding, fitPosterior, prior)</a></li><li><a href="#_sub2" class="code">function MLC = build(MLC)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(MLC,instance)</a></li><li><a href="#_sub4" class="code">function MLC = reset(MLC)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(MLC)</a></li><li><a href="#_sub6" class="code">function time = getTime(MLC)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MLTboxMulticlass.m">MLTboxMulticlass.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MLTboxMulticlass.html" class="code" title="">MLTboxMulticlass</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004         
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008         Learners; <span class="comment">%'discriminant': Discriminant analysis. | 'knn': k-nearest neighbors. | 'naivebayes': Naive Bayes.</span>
+0009         <span class="comment">% 'svm': SVM. | 'tree': Classification trees. | any Matlab template classifier</span>
+0010         Coding; <span class="comment">% Coding design 'onevsall' (default) | 'allpairs' | 'binarycomplete' | 'denserandom' | 'onevsone' | 'ordinal' | 'sparserandom' | 'ternarycomplete' | numeric matrix</span>
+0011         FitPosterior; <span class="comment">% Flag indicating whether to transform scores to posterior probabilities false or 0 (default) | true or 1</span>
+0012         Prior <span class="comment">% 'empirical' (default) or 'uniform'.  Prior probabilities for each class.</span>
+0013         models;
+0014         totalTime;
+0015         totalCount;
+0016     <span class="keyword">end</span>
+0017     
+0018     methods (Access = public)
+0019         <a name="_sub0" href="#_subfunctions" class="code">function MLC = MLTboxMulticlass(instanceSet, learners, coding, fitPosterior, prior)</a>
+0020             <span class="comment">%set default parameters</span>
+0021             MLC.Learners = <span class="string">'svm'</span>;
+0022             MLC.Coding=<span class="string">'onevsall'</span>;
+0023             MLC.FitPosterior=<span class="string">'off'</span>;
+0024             MLC.Prior=<span class="string">'empirical'</span>;
+0025             
+0026             <span class="keyword">if</span> nargin &gt; 0
+0027                 MLC.instanceSet = instanceSet;
+0028             <span class="keyword">end</span>
+0029             <span class="keyword">if</span> nargin &gt; 1
+0030                 MLC.Learners = learners;
+0031             <span class="keyword">end</span>
+0032             <span class="keyword">if</span> nargin &gt; 2
+0033                 MLC.Coding=coding;
+0034             <span class="keyword">end</span>
+0035             <span class="keyword">if</span> nargin &gt; 3
+0036                 MLC.FitPosterior=fitPosterior;
+0037             <span class="keyword">end</span>
+0038             <span class="keyword">if</span> nargin &gt; 4
+0039                 MLC.Prior=prior;
+0040             <span class="keyword">end</span>
+0041             MLC.totalTime = 0;
+0042             MLC.totalCount = 0;
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub1" href="#_subfunctions" class="code">function MLC = build(MLC)</a>
+0046             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0047             MLC.reset;
+0048             numLabels = MLC.instanceSet.getNumLabels;
+0049             uniqueLabels = unique(MLC.instanceSet.getLabels);
+0050             
+0051             <span class="comment">% ---- Multi-Class ----- %</span>
+0052             instances=MLC.instanceSet.instances;
+0053             labels=MLC.instanceSet.labels;
+0054             
+0055             <span class="comment">%t=templateSVM('KernelFunction','linear');</span>
+0056             MLC.models{1}=fitcecoc(instances,labels,<span class="string">'Coding'</span>, MLC.Coding,<span class="string">'FitPosterior'</span>, MLC.FitPosterior,<span class="string">'Prior'</span>,MLC.Prior,<span class="string">'Learners'</span>,MLC.Learners);
+0057         <span class="keyword">end</span>
+0058         
+0059         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(MLC,instance)</a>
+0060 
+0061             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0062             numModels = length(MLC.models);
+0063             [numinstance, ~] = size(instance);
+0064             <span class="comment">%scores = zeros(numModels,numinstance);</span>
+0065             
+0066             <span class="comment">% ---- Multi-class ----- %</span>
+0067             tic
+0068             [label,scores,loss] = predict(MLC.models{1},instance);
+0069             MLC.totalTime = MLC.totalTime + toc;
+0070             MLC.totalCount = MLC.totalCount + numinstance;
+0071             output = zeros(numinstance,1);
+0072             probabilities = zeros(numinstance,1);
+0073             <span class="comment">%we need these for ranking metrics (e.g. mAP)</span>
+0074             ranking = scores;
+0075             <span class="keyword">for</span> i=1:numinstance
+0076                 <span class="comment">%select the class with the highest probability</span>
+0077                 [prob, idx] = max(scores(i,:));
+0078                 uniqueLabels = unique(MLC.instanceSet.getLabels);
+0079                 <span class="comment">%output the label with highest probability</span>
+0080                 output(i,1) = uniqueLabels(idx);
+0081                 <span class="comment">%return the probability for the output label</span>
+0082                 probabilities(i,1) = prob;
+0083             <span class="keyword">end</span>
+0084         <span class="keyword">end</span>
+0085         
+0086         <a name="_sub3" href="#_subfunctions" class="code">function MLC = reset(MLC)</a>
+0087             <span class="comment">%delete all stored models</span>
+0088             MLC.models = {};
+0089         <span class="keyword">end</span>
+0090         
+0091         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(MLC)</a>
+0092             configInfo=sprintf(<span class="string">'MLTboxMulticlass\tCoding:%s\tFitPosterior:%s\tPrior:%s\n\tLearners:'</span>, MLC.Coding, MLC.FitPosterior,MLC.Prior);
+0093             disp(MLC.Learners)
+0094             <span class="comment">%configInfo = 'MLSVMClassifier (Config info not supported yet)';</span>
+0095         <span class="keyword">end</span>
+0096         
+0097                         
+0098         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MLC)</a>
+0099             time = MLC.totalTime/MLC.totalCount;
+0100         <span class="keyword">end</span>
+0101         
+0102     <span class="keyword">end</span>
+0103 <span class="keyword">end</span>
+0104</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.m b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.m
new file mode 100644
index 0000000..07c37e3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.m
@@ -0,0 +1,104 @@
+classdef MLTboxMulticlass < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+        
+    end
+    
+    properties
+        Learners; %'discriminant': Discriminant analysis. | 'knn': k-nearest neighbors. | 'naivebayes': Naive Bayes.
+        % 'svm': SVM. | 'tree': Classification trees. | any Matlab template classifier
+        Coding; % Coding design 'onevsall' (default) | 'allpairs' | 'binarycomplete' | 'denserandom' | 'onevsone' | 'ordinal' | 'sparserandom' | 'ternarycomplete' | numeric matrix
+        FitPosterior; % Flag indicating whether to transform scores to posterior probabilities false or 0 (default) | true or 1
+        Prior % 'empirical' (default) or 'uniform'.  Prior probabilities for each class.
+        models;
+        totalTime;
+        totalCount;
+    end
+    
+    methods (Access = public)
+        function MLC = MLTboxMulticlass(instanceSet, learners, coding, fitPosterior, prior)
+            %set default parameters
+            MLC.Learners = 'svm';
+            MLC.Coding='onevsall';
+            MLC.FitPosterior='off';
+            MLC.Prior='empirical';
+            
+            if nargin > 0
+                MLC.instanceSet = instanceSet;
+            end
+            if nargin > 1
+                MLC.Learners = learners;
+            end
+            if nargin > 2
+                MLC.Coding=coding;
+            end
+            if nargin > 3
+                MLC.FitPosterior=fitPosterior;
+            end
+            if nargin > 4
+                MLC.Prior=prior;
+            end
+            MLC.totalTime = 0;
+            MLC.totalCount = 0;
+        end
+        
+        function MLC = build(MLC)
+            %clear all from previous calls to "build"
+            MLC.reset;
+            numLabels = MLC.instanceSet.getNumLabels;
+            uniqueLabels = unique(MLC.instanceSet.getLabels);
+            
+            % ---- Multi-Class ----- %
+            instances=MLC.instanceSet.instances;
+            labels=MLC.instanceSet.labels;
+            
+            %t=templateSVM('KernelFunction','linear');
+            MLC.models{1}=fitcecoc(instances,labels,'Coding', MLC.Coding,'FitPosterior', MLC.FitPosterior,'Prior',MLC.Prior,'Learners',MLC.Learners);
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(MLC,instance)
+
+            %TODO:should print an error if 'build' has not been called
+            numModels = length(MLC.models);
+            [numinstance, ~] = size(instance);
+            %scores = zeros(numModels,numinstance);
+            
+            % ---- Multi-class ----- %
+            tic
+            [label,scores,loss] = predict(MLC.models{1},instance);
+            MLC.totalTime = MLC.totalTime + toc;
+            MLC.totalCount = MLC.totalCount + numinstance;
+            output = zeros(numinstance,1);
+            probabilities = zeros(numinstance,1);
+            %we need these for ranking metrics (e.g. mAP)
+            ranking = scores;
+            for i=1:numinstance
+                %select the class with the highest probability
+                [prob, idx] = max(scores(i,:));
+                uniqueLabels = unique(MLC.instanceSet.getLabels);
+                %output the label with highest probability
+                output(i,1) = uniqueLabels(idx);
+                %return the probability for the output label
+                probabilities(i,1) = prob;
+            end
+        end
+        
+        function MLC = reset(MLC)
+            %delete all stored models
+            MLC.models = {};
+        end
+        
+        function configInfo = getConfigInfo(MLC)
+            configInfo=sprintf('MLTboxMulticlass\tCoding:%s\tFitPosterior:%s\tPrior:%s\n\tLearners:', MLC.Coding, MLC.FitPosterior,MLC.Prior);
+            disp(MLC.Learners)
+            %configInfo = 'MLSVMClassifier (Config info not supported yet)';
+        end
+        
+                        
+        function time = getTime(MLC)
+            time = MLC.totalTime/MLC.totalCount;
+        end
+        
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.dot b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.dot
new file mode 100644
index 0000000..7256ede
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MLTboxMulticlass -> MLTboxMulticlass;
+
+  MLTboxMulticlass [URL="MLTboxMulticlass.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.html
new file mode 100644
index 0000000..4dbb14d
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@MLTboxMulticlass</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@MLTboxMulticlass">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLTboxMulticlass">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLTboxMulticlass</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MLTboxMulticlass" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MLTboxMulticlass.html" title="MLTboxMulticlass" alt="" coords="217,29,212,22,197,15,173,10,144,7,111,5,78,7,48,10,24,15,9,22,4,29,9,37,24,43,48,49,78,52,111,53,144,52,173,49,197,43,212,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.map b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.map
new file mode 100644
index 0000000..f63cb88
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.map
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diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/index.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/index.html
new file mode 100644
index 0000000..9c16ab8
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@MLTboxMulticlass</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@MLTboxMulticlass">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@MLTboxMulticlass">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@MLTboxMulticlass</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MLTboxMulticlass.html">MLTboxMulticlass</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.html b/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.html
new file mode 100644
index 0000000..c7cdfc3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.html
@@ -0,0 +1,104 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MaxChooser</title>
+  <meta name="keywords" content="MaxChooser">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MaxChooser</a> &gt; MaxChooser.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MaxChooser&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MaxChooser
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MaxChooser.html" class="code" title="">MaxChooser</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MaxChooser.html" class="code" title="">MaxChooser</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function MaxChooser =MaxChooser(instanceSet)</a></li><li><a href="#_sub2" class="code">function MaxChooser = build(MaxChooser)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(MaxChooser,instance)</a></li><li><a href="#_sub4" class="code">function MaxChooser = reset(MaxChooser)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(MaxChooser)</a></li><li><a href="#_sub6" class="code">function time = getTime(MaxChooser)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MaxChooser.m">MaxChooser.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MaxChooser.html" class="code" title="">MaxChooser</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008       
+0009     <span class="keyword">end</span>
+0010     
+0011     methods (Access = public)
+0012         <a name="_sub0" href="#_subfunctions" class="code">function MaxChooser =MaxChooser(instanceSet)</a>
+0013             <span class="keyword">if</span> nargin &gt; 0
+0014                 MaxChooser.instanceSet = instanceSet;
+0015             <span class="keyword">end</span>
+0016            
+0017         <span class="keyword">end</span>
+0018         
+0019         <a name="_sub1" href="#_subfunctions" class="code">function MaxChooser = build(MaxChooser)</a>
+0020             
+0021         <span class="keyword">end</span>
+0022         
+0023         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(MaxChooser,instance)</a>
+0024             
+0025             dd_ins=instance;
+0026             N = size(instance,1);
+0027             pred_lab=zeros(N,1);
+0028             <span class="keyword">for</span> i=1:N
+0029                 [v,idx]=max(dd_ins(i,:));                
+0030                 pred_lab(i)=idx;   
+0031                 ranking(i,:) = dd_ins(i,:);
+0032             <span class="keyword">end</span>
+0033             
+0034             output = pred_lab;<span class="comment">%sum(pred_lab)/length(pred_lab)</span>
+0035             probabilities=zeros(N,1);
+0036 <span class="comment">%             ranking=zeros(N,1);</span>
+0037         <span class="keyword">end</span>
+0038         
+0039         <a name="_sub3" href="#_subfunctions" class="code">function MaxChooser = reset(MaxChooser)</a>
+0040             <span class="comment">%delete all stored models</span>
+0041         <span class="keyword">end</span>
+0042         
+0043         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(MaxChooser)</a>
+0044             configInfo = sprintf(<span class="string">'MaxChooser'</span>);
+0045         <span class="keyword">end</span>
+0046         
+0047                         
+0048         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MaxChooser)</a>
+0049             time = 0;
+0050         <span class="keyword">end</span>
+0051                 
+0052     <span class="keyword">end</span>
+0053 <span class="keyword">end</span>
+0054</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.m b/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.m
new file mode 100644
index 0000000..4d90bd9
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.m
@@ -0,0 +1,54 @@
+classdef MaxChooser < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties
+      
+    end
+    
+    methods (Access = public)
+        function MaxChooser =MaxChooser(instanceSet)
+            if nargin > 0
+                MaxChooser.instanceSet = instanceSet;
+            end
+           
+        end
+        
+        function MaxChooser = build(MaxChooser)
+            
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(MaxChooser,instance)
+            
+            dd_ins=instance;
+            N = size(instance,1);
+            pred_lab=zeros(N,1);
+            for i=1:N
+                [v,idx]=max(dd_ins(i,:));                
+                pred_lab(i)=idx;   
+                ranking(i,:) = dd_ins(i,:);
+            end
+            
+            output = pred_lab;%sum(pred_lab)/length(pred_lab)
+            probabilities=zeros(N,1);
+%             ranking=zeros(N,1);
+        end
+        
+        function MaxChooser = reset(MaxChooser)
+            %delete all stored models           
+        end
+        
+        function configInfo = getConfigInfo(MaxChooser)
+            configInfo = sprintf('MaxChooser');
+        end
+        
+                        
+        function time = getTime(MaxChooser)
+            time = 0;
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/graph.dot b/doc/+eegtoolkit/+classification/@MaxChooser/graph.dot
new file mode 100644
index 0000000..9227aa8
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MaxChooser -> MaxChooser;
+
+  MaxChooser [URL="MaxChooser.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/graph.html b/doc/+eegtoolkit/+classification/@MaxChooser/graph.html
new file mode 100644
index 0000000..d822156
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@MaxChooser</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@MaxChooser">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MaxChooser">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MaxChooser&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@MaxChooser</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MaxChooser" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MaxChooser.html" title="MaxChooser" alt="" coords="155,29,152,22,141,15,124,10,103,7,80,5,57,7,36,10,19,15,8,22,5,29,8,37,19,43,36,49,57,52,80,53,103,52,124,49,141,43,152,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/graph.map b/doc/+eegtoolkit/+classification/@MaxChooser/graph.map
new file mode 100644
index 0000000..36ff2c4
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/graph.map
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diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/index.html b/doc/+eegtoolkit/+classification/@MaxChooser/index.html
new file mode 100644
index 0000000..6a64ed3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@MaxChooser/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@MaxChooser</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@MaxChooser">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@MaxChooser">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
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+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
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+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MaxChooser&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@MaxChooser</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MaxChooser.html">MaxChooser</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+classification/@SBLR/SBLR.html b/doc/+eegtoolkit/+classification/@SBLR/SBLR.html
new file mode 100644
index 0000000..d82eff8
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/SBLR.html
@@ -0,0 +1,138 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of SBLR</title>
+  <meta name="keywords" content="SBLR">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@SBLR</a> &gt; SBLR.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SBLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>SBLR
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SBLR.html" class="code" title="">SBLR</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SBLR.html" class="code" title="">SBLR</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function SBLR = SBLR(instanceSet)</a></li><li><a href="#_sub2" class="code">function SBLR = build(SBLR)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(SBLR,instance)</a></li><li><a href="#_sub4" class="code">function SBLR = reset(SBLR)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(SBLR)</a></li><li><a href="#_sub6" class="code">function time = getTime(MLR_Classifier)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="SBLR.m">SBLR.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="SBLR.html" class="code" title="">SBLR</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties
+0008        <span class="comment">%Coding; % Coding design 'onevsall' (default) | 'allpairs' | 'binarycomplete' | 'denserandom' | 'onevsone' | 'ordinal' | 'sparserandom' | 'ternarycomplete' | numeric matrix</span>
+0009        <span class="comment">%FitPosterior; % Flag indicating whether to transform scores to posterior probabilities false or 0 (default) | true or 1</span>
+0010        <span class="comment">%Prior % 'empirical' (default) or 'uniform'.  Prior probabilities for each class.</span>
+0011        models;
+0012        Wmatrix;
+0013     <span class="keyword">end</span>
+0014     
+0015     methods (Access = public)
+0016         <a name="_sub0" href="#_subfunctions" class="code">function SBLR = SBLR(instanceSet)</a>
+0017             <span class="comment">%set default parameters</span>
+0018             <span class="keyword">if</span> nargin &gt; 0
+0019                 SBLR.instanceSet = instanceSet;
+0020             <span class="keyword">end</span>                   
+0021         <span class="keyword">end</span>
+0022         
+0023         <a name="_sub1" href="#_subfunctions" class="code">function SBLR = build(SBLR)</a>
+0024             <span class="comment">%clear all from previous calls to &quot;build&quot;</span>
+0025             SBLR.reset;
+0026             numLabels = SBLR.instanceSet.getNumLabels;
+0027             uniqueLabels = unique(SBLR.instanceSet.getLabels);
+0028            
+0029             <span class="comment">% ---- Multi-Class ----- %</span>
+0030             instances=SBLR.instanceSet.instances;
+0031             labels=SBLR.instanceSet.labels;
+0032             [~,Nfeat] = size(instances)
+0033             size(instances)
+0034             <span class="comment">%X = instances*instances;</span>
+0035           <span class="comment">%[w, ix_eff, W, AX] = slr_learning_var2(labels, instances,'nlearn', 100, 'nstep', 10);</span>
+0036           [w, ix_eff, W, AXall] = smlr_learning(labels, instances, Nfeat,<span class="string">'nlearn'</span>, 0,<span class="string">'gamma0'</span>, 0);<span class="comment">%,...</span>
+0037               <span class="comment">%'wdisp_mode', 'off', 'nlearn',10,'mean_mode', 'none', 'scale_mode', 'none');%, ...</span>
+0038             <span class="comment">%'wdisplay', wdisp_mode, 'wmaxiter', wmaxiter', 'nlearn', Nlearn, 'nstep', Nstep,...</span>
+0039             <span class="comment">%'amax', AMAX, 'isplot', isplot', 'gamma0', gamma0);</span>
+0040         
+0041           SBLR.Wmatrix = reshape(w, [Nfeat, 5]);           
+0042         
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(SBLR,instance)</a>
+0046             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0047             <span class="comment">%output = predicted class</span>
+0048             <span class="comment">%probabilities = probability for predicted class</span>
+0049             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0050             
+0051             
+0052             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0053 <span class="comment">%             numModels = length(MLSVM.models);</span>
+0054             [numinstance, ~] = size(instance);
+0055             <span class="comment">%scores = zeros(numModels,numinstance);</span>
+0056             
+0057             [output, Pte] = calc_label(instance, SBLR.Wmatrix);
+0058             <span class="comment">% ---- One (vs) All -----%</span>
+0059 <span class="comment">%              for i=1:numModels</span>
+0060 <span class="comment">%                  %predict using the stored models</span>
+0061 <span class="comment">%                  [label,score,cost] = predict(LDA.models{i},instance);</span>
+0062 <span class="comment">%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');</span>
+0063 <span class="comment">%                 %store probability for each class</span>
+0064 <span class="comment">%                 scores(i,:) = score(:,1);</span>
+0065 <span class="comment">%             end</span>
+0066 
+0067             ranking=zeros(5,1)';
+0068             probabilities=0;          
+0069         <span class="keyword">end</span>
+0070         
+0071         <a name="_sub3" href="#_subfunctions" class="code">function SBLR = reset(SBLR)</a>
+0072             <span class="comment">%delete all stored models</span>
+0073             SBLR.models = {};
+0074             SBLR.Wmatrix=[];
+0075         <span class="keyword">end</span>
+0076         
+0077         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(SBLR)</a>
+0078            
+0079             configInfo = <span class="string">'SBLR_Classifier (Config info not supported yet)'</span>;
+0080         <span class="keyword">end</span>
+0081         
+0082         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(MLR_Classifier)</a>
+0083             time = 0;
+0084         <span class="keyword">end</span>
+0085                 
+0086     <span class="keyword">end</span>
+0087 <span class="keyword">end</span>
+0088</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SBLR/SBLR.m b/doc/+eegtoolkit/+classification/@SBLR/SBLR.m
new file mode 100644
index 0000000..30f315d
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/SBLR.m
@@ -0,0 +1,88 @@
+classdef SBLR < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties
+       %Coding; % Coding design 'onevsall' (default) | 'allpairs' | 'binarycomplete' | 'denserandom' | 'onevsone' | 'ordinal' | 'sparserandom' | 'ternarycomplete' | numeric matrix
+       %FitPosterior; % Flag indicating whether to transform scores to posterior probabilities false or 0 (default) | true or 1
+       %Prior % 'empirical' (default) or 'uniform'.  Prior probabilities for each class. 
+       models;
+       Wmatrix;
+    end
+    
+    methods (Access = public)
+        function SBLR = SBLR(instanceSet)
+            %set default parameters
+            if nargin > 0
+                SBLR.instanceSet = instanceSet;
+            end                   
+        end
+        
+        function SBLR = build(SBLR)
+            %clear all from previous calls to "build"
+            SBLR.reset;
+            numLabels = SBLR.instanceSet.getNumLabels;
+            uniqueLabels = unique(SBLR.instanceSet.getLabels);
+           
+            % ---- Multi-Class ----- %
+            instances=SBLR.instanceSet.instances;
+            labels=SBLR.instanceSet.labels;
+            [~,Nfeat] = size(instances)
+            size(instances)
+            %X = instances*instances;
+          %[w, ix_eff, W, AX] = slr_learning_var2(labels, instances,'nlearn', 100, 'nstep', 10);
+          [w, ix_eff, W, AXall] = smlr_learning(labels, instances, Nfeat,'nlearn', 0,'gamma0', 0);%,...
+              %'wdisp_mode', 'off', 'nlearn',10,'mean_mode', 'none', 'scale_mode', 'none');%, ...
+            %'wdisplay', wdisp_mode, 'wmaxiter', wmaxiter', 'nlearn', Nlearn, 'nstep', Nstep,...
+            %'amax', AMAX, 'isplot', isplot', 'gamma0', gamma0);
+        
+          SBLR.Wmatrix = reshape(w, [Nfeat, 5]);           
+        
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(SBLR,instance)
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            
+            %TODO:should print an error if 'build' has not been called
+%             numModels = length(MLSVM.models);
+            [numinstance, ~] = size(instance);
+            %scores = zeros(numModels,numinstance);                  
+            
+            [output, Pte] = calc_label(instance, SBLR.Wmatrix);
+            % ---- One (vs) All -----%
+%              for i=1:numModels
+%                  %predict using the stored models
+%                  [label,score,cost] = predict(LDA.models{i},instance);
+%                  %libsvmpredict(eye(numinstance,1),instance, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = score(:,1);
+%             end
+
+            ranking=zeros(5,1)';
+            probabilities=0;          
+        end
+        
+        function SBLR = reset(SBLR)
+            %delete all stored models
+            SBLR.models = {};
+            SBLR.Wmatrix=[];
+        end
+        
+        function configInfo = getConfigInfo(SBLR)
+           
+            configInfo = 'SBLR_Classifier (Config info not supported yet)';
+        end
+        
+        function time = getTime(MLR_Classifier)
+            time = 0;
+        end
+                
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@SBLR/graph.dot b/doc/+eegtoolkit/+classification/@SBLR/graph.dot
new file mode 100644
index 0000000..6ecd254
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  SBLR -> SBLR;
+
+  SBLR [URL="SBLR.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SBLR/graph.html b/doc/+eegtoolkit/+classification/@SBLR/graph.html
new file mode 100644
index 0000000..77be386
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@SBLR</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@SBLR">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@SBLR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SBLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@SBLR</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@SBLR" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="SBLR.html" title="SBLR" alt="" coords="91,29,89,22,83,15,73,10,61,7,48,5,35,7,23,10,13,15,7,22,5,29,7,37,13,43,23,49,35,52,48,53,61,52,73,49,83,43,89,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SBLR/graph.map b/doc/+eegtoolkit/+classification/@SBLR/graph.map
new file mode 100644
index 0000000..bc7b84e
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="SBLR.html" title="SBLR" alt="" coords="91,29,89,22,83,15,73,10,61,7,48,5,35,7,23,10,13,15,7,22,5,29,7,37,13,43,23,49,35,52,48,53,61,52,73,49,83,43,89,37">
diff --git a/doc/+eegtoolkit/+classification/@SBLR/graph.png b/doc/+eegtoolkit/+classification/@SBLR/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+classification/@SBLR/index.html b/doc/+eegtoolkit/+classification/@SBLR/index.html
new file mode 100644
index 0000000..00e437a
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SBLR/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@SBLR</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@SBLR">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@SBLR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SBLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@SBLR</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="SBLR.html">SBLR</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SMFA/SMFA.html b/doc/+eegtoolkit/+classification/@SMFA/SMFA.html
new file mode 100644
index 0000000..cd760e3
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SMFA/SMFA.html
@@ -0,0 +1,193 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of SMFA</title>
+  <meta name="keywords" content="SMFA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@SMFA</a> &gt; SMFA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SMFA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>SMFA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SMFA.html" class="code" title="">SMFA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SMFA.html" class="code" title="">SMFA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function SMFA = SMFA(instanceSet,NumS,S,kInt,kPen)</a></li><li><a href="#_sub2" class="code">function SMFA = build(SMFA)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(SMFA,instance)</a></li><li><a href="#_sub4" class="code">function SMFA = reset(SMFA)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(SMFA)</a></li><li><a href="#_sub6" class="code">function time = getTime(SMFA)</a></li><li><a href="#_sub7" class="code">function Proj_W=pca_func(MLR,data)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="SMFA.m">SMFA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="SMFA.html" class="code" title="">SMFA</a> &lt; eegtoolkit.classification.ClassifierBase
+0002     
+0003     properties (Constant)
+0004 
+0005     <span class="keyword">end</span>
+0006     
+0007     properties (Access = public)
+0008       W_SMFA;
+0009       PCA_mat;
+0010       trainFeat;
+0011       NumSubclasses;
+0012       SigmaCoeff;
+0013       kInt;
+0014       kPen;
+0015     <span class="keyword">end</span>
+0016     
+0017     methods (Access = public)
+0018         <a name="_sub0" href="#_subfunctions" class="code">function SMFA = SMFA(instanceSet,NumS,S,kInt,kPen)</a><span class="comment">%,NumSubclasses,SigmaCoeff,kInt,kPen)</span>
+0019             <span class="keyword">if</span> nargin == 1
+0020                 SMFA.instanceSet = instanceSet;
+0021             <span class="keyword">else</span>
+0022                 SMFA.NumSubclasses = NumS;
+0023                 SMFA.SigmaCoeff = S;
+0024                 SMFA.kInt = kInt;
+0025                 SMFA.kPen = kPen;
+0026             <span class="keyword">end</span>
+0027            
+0028         <span class="keyword">end</span>
+0029             
+0030         
+0031         <a name="_sub1" href="#_subfunctions" class="code">function SMFA = build(SMFA)</a>
+0032             SMFA.reset();
+0033             data = SMFA.instanceSet.getInstances;
+0034             data = data';  
+0035             labels = SMFA.instanceSet.getLabels;    
+0036             unique(labels)           
+0037             numTrials = length(labels);
+0038 
+0039             PCA_W=SMFA.pca_func(data);
+0040 <span class="comment">%             PCA_W=eye(size(data,1));</span>
+0041             train_Data=PCA_W'*data; 
+0042             
+0043 <span class="comment">%             Sigma = SMFA_Classifier.SigmaCoeff;</span>
+0044             NSubClasses = SMFA.NumSubclasses;
+0045             D=pdist2(train_Data',train_Data');
+0046 <span class="comment">%             STrain = SGE_GramMatrix(train_Data,'gau',Sigma*mean(D(:)));</span>
+0047             STrain = 1-(D/max(D(:)));
+0048             
+0049             pt=0;
+0050             ct=0;
+0051             ClustersOfClasses = SGE_SubclassExtract(train_Data,labels,NSubClasses,pt,ct);
+0052             [yyTrain,~,~] = SGE_SubclassLabels(ClustersOfClasses,labels);
+0053            
+0054             
+0055             Par.mode = <span class="string">'SMFA'</span>;
+0056             Par.SimilMatrix = STrain;
+0057             Par.kInt = SMFA.kInt;
+0058             Par.kPen = SMFA.kPen;
+0059             dim = min([Par.kPen,size(train_Data,1)]);
+0060             
+0061             [W,Wp] = SGE_GraphConstruct(yyTrain,Par);
+0062             [TransMatrix,~] = SGE_Mapping(train_Data,dim,W,Wp);
+0063             SMFA.W_SMFA = TransMatrix;
+0064             SMFA.PCA_mat=PCA_W;
+0065             mtrainFeat=SGE_Projection(train_Data,1:dim,TransMatrix);
+0066             SMFA.trainFeat=mtrainFeat;                       
+0067 <span class="comment">%             figure,gplotmatrix(mtrainFeat',[],labels)</span>
+0068         <span class="keyword">end</span>
+0069         
+0070         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(SMFA,instance)</a>
+0071             
+0072             N = size(instance,1);            
+0073             instance = instance'; 
+0074             
+0075             test_Data=SMFA.PCA_mat'*instance;               
+0076 <span class="comment">%             test_Data=[ones(1,N);test_Data];</span>
+0077             testFeat=SMFA.W_SMFA'*test_Data;
+0078 <span class="comment">%             output=knnclassify(testFeat',SMFA_Classifier.trainFeat',SMFA_Classifier.instanceSet.getLabels,5,'euclidean');</span>
+0079             X = SMFA.trainFeat;
+0080             y = SMFA.instanceSet.getLabels;
+0081             
+0082             <span class="comment">%Nearest Centroid</span>
+0083             [~,output] = SGE_Classification(X,y',testFeat,0,<span class="string">'euc'</span>);
+0084             
+0085 <span class="comment">%             %SVM Linear</span>
+0086 <span class="comment">%             [~,output] = SGE_Classification(X,y',testFeat,[1,1,1,0,1],'euc');</span>
+0087 
+0088 <span class="comment">%             %SVM RBF</span>
+0089 <span class="comment">%             [~,output] = SGE_Classification(X,y',testFeat,[2,3,2/size(X,1),0,1],'euc');</span>
+0090             
+0091             output = output(1,:)';
+0092             probabilities=zeros(N,1);
+0093             ranking=zeros(N,1);
+0094 <span class="comment">%             figure,gplotmatrix(testFeat',[],output)</span>
+0095           
+0096         <span class="keyword">end</span>
+0097         
+0098         <a name="_sub3" href="#_subfunctions" class="code">function SMFA = reset(SMFA)</a>
+0099             <span class="comment">%delete all stored models</span>
+0100             SMFA.W_SMFA=[];
+0101             SMFA.PCA_mat=[];
+0102             SMFA.trainFeat=[];
+0103         <span class="keyword">end</span>
+0104         
+0105         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(SMFA)</a>
+0106             configInfo = sprintf(<span class="string">'MLR_Classifier'</span>);
+0107         <span class="keyword">end</span>
+0108         
+0109                         
+0110         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(SMFA)</a>
+0111             
+0112         <span class="keyword">end</span>
+0113                 
+0114     <span class="keyword">end</span>
+0115     methods (Access = private)
+0116         <a name="_sub6" href="#_subfunctions" class="code">function Proj_W=pca_func(MLR,data)</a>
+0117             Proj_W=[];
+0118             meanData=mean(data,2);
+0119             data=data-repmat(meanData,1,size(data,2));
+0120             <span class="comment">% stdVar=std(data')';</span>
+0121             <span class="comment">% staData=(data-repmat(meanData,1,size(data,2)))./repmat(stdVar,1,size(data,2));</span>
+0122             <span class="comment">% data=staData;</span>
+0123             [V,S]=eig(data'*data);
+0124             [sorted_diagS,sorted_rank]=sort(diag(S),<span class="string">'descend'</span>);
+0125             sorted_S=diag(sorted_diagS);
+0126             V=V(:,sorted_rank);
+0127             r=rank(sorted_S);
+0128             S1=sorted_S(1:r,1:r);
+0129             V1=V(:,1:r);
+0130             U=data*V1*S1^(-0.5);
+0131             <span class="comment">%[sorted_S,sorted_rank]=sort(diag(S),'descend');</span>
+0132             All_energy=sum(diag(S1));
+0133             sorted_energy=diag(S1);
+0134             <span class="keyword">for</span> j=1:r
+0135                 <span class="keyword">if</span> (sum(sorted_energy(1:j))/All_energy)&gt;0.99
+0136                     <span class="keyword">break</span>
+0137                 <span class="keyword">end</span>
+0138             <span class="keyword">end</span>
+0139             Proj_W=U(:,1:j);
+0140         <span class="keyword">end</span>
+0141     <span class="keyword">end</span>
+0142 <span class="keyword">end</span>
+0143</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SMFA/SMFA.m b/doc/+eegtoolkit/+classification/@SMFA/SMFA.m
new file mode 100644
index 0000000..f16f2c7
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SMFA/SMFA.m
@@ -0,0 +1,143 @@
+classdef SMFA < eegtoolkit.classification.ClassifierBase
+    
+    properties (Constant)
+
+    end
+    
+    properties (Access = public)
+      W_SMFA;
+      PCA_mat;
+      trainFeat;
+      NumSubclasses;
+      SigmaCoeff;
+      kInt;
+      kPen;
+    end
+    
+    methods (Access = public)
+        function SMFA = SMFA(instanceSet,NumS,S,kInt,kPen)%,NumSubclasses,SigmaCoeff,kInt,kPen)
+            if nargin == 1
+                SMFA.instanceSet = instanceSet;
+            else
+                SMFA.NumSubclasses = NumS;
+                SMFA.SigmaCoeff = S;
+                SMFA.kInt = kInt;
+                SMFA.kPen = kPen;
+            end
+           
+        end
+            
+        
+        function SMFA = build(SMFA)
+            SMFA.reset();
+            data = SMFA.instanceSet.getInstances;
+            data = data';  
+            labels = SMFA.instanceSet.getLabels;    
+            unique(labels)           
+            numTrials = length(labels);
+
+            PCA_W=SMFA.pca_func(data);
+%             PCA_W=eye(size(data,1));
+            train_Data=PCA_W'*data; 
+            
+%             Sigma = SMFA_Classifier.SigmaCoeff;
+            NSubClasses = SMFA.NumSubclasses;
+            D=pdist2(train_Data',train_Data');
+%             STrain = SGE_GramMatrix(train_Data,'gau',Sigma*mean(D(:)));
+            STrain = 1-(D/max(D(:)));
+            
+            pt=0;
+            ct=0;
+            ClustersOfClasses = SGE_SubclassExtract(train_Data,labels,NSubClasses,pt,ct);
+            [yyTrain,~,~] = SGE_SubclassLabels(ClustersOfClasses,labels);
+           
+            
+            Par.mode = 'SMFA';
+            Par.SimilMatrix = STrain;
+            Par.kInt = SMFA.kInt;
+            Par.kPen = SMFA.kPen;
+            dim = min([Par.kPen,size(train_Data,1)]);
+            
+            [W,Wp] = SGE_GraphConstruct(yyTrain,Par);
+            [TransMatrix,~] = SGE_Mapping(train_Data,dim,W,Wp);
+            SMFA.W_SMFA = TransMatrix;
+            SMFA.PCA_mat=PCA_W;
+            mtrainFeat=SGE_Projection(train_Data,1:dim,TransMatrix);
+            SMFA.trainFeat=mtrainFeat;                       
+%             figure,gplotmatrix(mtrainFeat',[],labels)
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(SMFA,instance)
+            
+            N = size(instance,1);            
+            instance = instance'; 
+            
+            test_Data=SMFA.PCA_mat'*instance;               
+%             test_Data=[ones(1,N);test_Data]; 
+            testFeat=SMFA.W_SMFA'*test_Data;
+%             output=knnclassify(testFeat',SMFA_Classifier.trainFeat',SMFA_Classifier.instanceSet.getLabels,5,'euclidean');  
+            X = SMFA.trainFeat;
+            y = SMFA.instanceSet.getLabels;
+            
+            %Nearest Centroid
+            [~,output] = SGE_Classification(X,y',testFeat,0,'euc');
+            
+%             %SVM Linear
+%             [~,output] = SGE_Classification(X,y',testFeat,[1,1,1,0,1],'euc');
+
+%             %SVM RBF
+%             [~,output] = SGE_Classification(X,y',testFeat,[2,3,2/size(X,1),0,1],'euc');
+            
+            output = output(1,:)';
+            probabilities=zeros(N,1);
+            ranking=zeros(N,1);
+%             figure,gplotmatrix(testFeat',[],output)
+          
+        end
+        
+        function SMFA = reset(SMFA)
+            %delete all stored models 
+            SMFA.W_SMFA=[];
+            SMFA.PCA_mat=[];
+            SMFA.trainFeat=[];
+        end
+        
+        function configInfo = getConfigInfo(SMFA)
+            configInfo = sprintf('MLR_Classifier');
+        end
+        
+                        
+        function time = getTime(SMFA)
+            
+        end
+                
+    end
+    methods (Access = private)
+        function Proj_W=pca_func(MLR,data)
+            Proj_W=[];
+            meanData=mean(data,2);
+            data=data-repmat(meanData,1,size(data,2));
+            % stdVar=std(data')';
+            % staData=(data-repmat(meanData,1,size(data,2)))./repmat(stdVar,1,size(data,2));
+            % data=staData;
+            [V,S]=eig(data'*data);
+            [sorted_diagS,sorted_rank]=sort(diag(S),'descend');
+            sorted_S=diag(sorted_diagS);
+            V=V(:,sorted_rank);
+            r=rank(sorted_S);
+            S1=sorted_S(1:r,1:r);
+            V1=V(:,1:r);
+            U=data*V1*S1^(-0.5);
+            %[sorted_S,sorted_rank]=sort(diag(S),'descend');
+            All_energy=sum(diag(S1));
+            sorted_energy=diag(S1);
+            for j=1:r
+                if (sum(sorted_energy(1:j))/All_energy)>0.99
+                    break
+                end
+            end
+            Proj_W=U(:,1:j);
+        end
+    end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@SMFA/graph.dot b/doc/+eegtoolkit/+classification/@SMFA/graph.dot
new file mode 100644
index 0000000..125d60e
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SMFA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  SMFA -> SMFA;
+
+  SMFA [URL="SMFA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SMFA/graph.html b/doc/+eegtoolkit/+classification/@SMFA/graph.html
new file mode 100644
index 0000000..d7fccb1
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SMFA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+classification/@SMFA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@SMFA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@SMFA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SMFA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+classification/@SMFA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@SMFA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="SMFA.html" title="SMFA" alt="" coords="99,29,97,22,90,15,80,10,66,7,52,5,38,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,38,52,52,53,66,52,80,49,90,43,97,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@SMFA/graph.map b/doc/+eegtoolkit/+classification/@SMFA/graph.map
new file mode 100644
index 0000000..d632bbb
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@SMFA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="SMFA.html" title="SMFA" alt="" coords="99,29,97,22,90,15,80,10,66,7,52,5,38,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,38,52,52,53,66,52,80,49,90,43,97,37">
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diff --git a/doc/+eegtoolkit/+classification/@SMFA/index.html b/doc/+eegtoolkit/+classification/@SMFA/index.html
new file mode 100644
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+++ b/doc/+eegtoolkit/+classification/@SMFA/index.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+classification/@SMFA</title>
+  <meta name="keywords" content="./+eegtoolkit/+classification/@SMFA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@SMFA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SMFA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+classification/@SMFA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="SMFA.html">SMFA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.html b/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.html
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--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.html
@@ -0,0 +1,455 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Experimenter</title>
+  <meta name="keywords" content="Experimenter">
+  <meta name="description" content="EXPERIMENTER class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+experiment</a> &gt; <a href="#">@Experimenter</a> &gt; Experimenter.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@Experimenter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Experimenter
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>EXPERIMENTER class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> EXPERIMENTER class
+ Wraps all the necessary objects for performing an experiment. 
+Before running an experiment all the required properties must be set.
+ Required:
+ - session
+ - featextraction
+ - evalMethod
+ - classification
+ Optional:
+ - featselection
+ - aggregator
+ - preprocessing
+
+ to run the experiment execute the &quot;run()&quot; method.
+ Example:
+ experiment = eegtoolkit.experiment.Experimenter;
+ experiment.session = eegtoolkit.util.Session;
+ experiment.session.loadSubject(1);
+ experiment.transformer = eegtoolkit.featextraction.PWelch;
+ experiment.extractor = eegtoolkit.featselection.FEAST;
+ experiment.classification = eegtoolkit.classification.LIBSVM;
+ experiment.evalMethod = experiment.evalMethod.EVAL_METHOD_LOSO;
+ experiment.run;
+ results = experiment.results;
+ confmatrix = results{1}.getConfusionMatrix;</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Experimenter.html" class="code" title="">Experimenter</a>	EXPERIMENTER class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Experimenter.html" class="code" title="">Experimenter</a>	EXPERIMENTER class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function E = Experimenter(evalMethod)</a></li><li><a href="#_sub2" class="code">function E = run(E,varargin)</a></li><li><a href="#_sub3" class="code">function itrs = getITR(E)</a></li><li><a href="#_sub4" class="code">function time = getTime(E)</a></li><li><a href="#_sub5" class="code">function info = getExperimentInfo(E)</a></li><li><a href="#_sub6" class="code">function E = checkCompatibility(E)</a></li><li><a href="#_sub7" class="code">function E = leaveOneOutCV(E)</a></li><li><a href="#_sub8" class="code">function E = kfoldCrossValidation(E,instanceSet,numFolds)</a></li><li><a href="#_sub9" class="code">function resultSet = leaveOneSubjectOut(E, subjectid, instanceSet)</a></li><li><a href="#_sub10" class="code">function resultSet = leaveOneSubjectOutLeaveOneBlockOut(E, instanceSet)</a></li><li><a href="#_sub11" class="code">function resultSet = leaveOneSessionOut(E, sessionId, instanceSet)</a></li><li><a href="#_sub12" class="code">function resultSet = leaveOneSubjectOutFast(E, subjectid, instanceSet)</a></li><li><a href="#_sub13" class="code">function resultSet = splitTest(E,trainIDx,testIDx, instanceSet)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Experimenter.m">Experimenter.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% EXPERIMENTER class</span>
+0002 <span class="comment">% Wraps all the necessary objects for performing an experiment.</span>
+0003 <span class="comment">%Before running an experiment all the required properties must be set.</span>
+0004 <span class="comment">% Required:</span>
+0005 <span class="comment">% - session</span>
+0006 <span class="comment">% - featextraction</span>
+0007 <span class="comment">% - evalMethod</span>
+0008 <span class="comment">% - classification</span>
+0009 <span class="comment">% Optional:</span>
+0010 <span class="comment">% - featselection</span>
+0011 <span class="comment">% - aggregator</span>
+0012 <span class="comment">% - preprocessing</span>
+0013 <span class="comment">%</span>
+0014 <span class="comment">% to run the experiment execute the &quot;run()&quot; method.</span>
+0015 <span class="comment">% Example:</span>
+0016 <span class="comment">% experiment = eegtoolkit.experiment.Experimenter;</span>
+0017 <span class="comment">% experiment.session = eegtoolkit.util.Session;</span>
+0018 <span class="comment">% experiment.session.loadSubject(1);</span>
+0019 <span class="comment">% experiment.transformer = eegtoolkit.featextraction.PWelch;</span>
+0020 <span class="comment">% experiment.extractor = eegtoolkit.featselection.FEAST;</span>
+0021 <span class="comment">% experiment.classification = eegtoolkit.classification.LIBSVM;</span>
+0022 <span class="comment">% experiment.evalMethod = experiment.evalMethod.EVAL_METHOD_LOSO;</span>
+0023 <span class="comment">% experiment.run;</span>
+0024 <span class="comment">% results = experiment.results;</span>
+0025 <span class="comment">% confmatrix = results{1}.getConfusionMatrix;</span>
+0026 classdef <a href="Experimenter.html" class="code" title="">Experimenter</a> &lt; handle
+0027     properties (Constant)
+0028         EVAL_METHOD_LOOCV = 0; <span class="comment">% Leave One Out Cross-Validation</span>
+0029         EVAL_METHOD_LOSO = 1; <span class="comment">% Leave One Subject Out</span>
+0030         EVAL_METHOD_LOBO = 2;
+0031         EVAL_METHOD_SPLIT = 3;
+0032         EVAL_METHOD_XFOLD_CV = 4;
+0033         EVAL_METHOD_LOSO_LOBO = 5;
+0034     <span class="keyword">end</span>
+0035     
+0036     properties (Access = public)
+0037         session; <span class="comment">% The Session object. Trials must be loaded before run() is executed</span>
+0038         preprocessing;
+0039         featextraction; <span class="comment">% A transformer object</span>
+0040         aggregator;
+0041         featselection; <span class="comment">% An extractor object</span>
+0042         evalMethod; <span class="comment">% The evaluation method</span>
+0043         classification; <span class="comment">% A classifier object</span>
+0044         results; <span class="comment">% A cell array containing objects of the 'ResultEvaluator' class.</span>
+0045         trainresults;
+0046         subjectids;
+0047         sessionids;
+0048     <span class="keyword">end</span>
+0049     
+0050     methods
+0051         <a name="_sub0" href="#_subfunctions" class="code">function E = Experimenter(evalMethod)</a>
+0052             <span class="keyword">if</span> nargin &gt; 0
+0053                 E.evalMethod = evalMethod;
+0054             <span class="keyword">else</span> E.evalMethod = 0;
+0055             <span class="keyword">end</span>
+0056             E.results = {};
+0057         <span class="keyword">end</span>
+0058         <a name="_sub1" href="#_subfunctions" class="code">function E = run(E,varargin)</a>
+0059             <span class="keyword">if</span>(length(varargin)==1)
+0060                 numFolds = varargin{1};
+0061             <span class="keyword">elseif</span>(length(varargin)==2)
+0062                 trainIDx = varargin{1};
+0063                 testIDx = varargin{2};
+0064             <span class="keyword">end</span>
+0065             <span class="comment">% Runs an experiment</span>
+0066             E.checkCompatibility;
+0067             E.subjectids = E.session.subjectids;
+0068             E.sessionids = E.session.sessionids;
+0069             trials = {};
+0070             <span class="keyword">for</span> i=1:length(E.session.trials)
+0071                 trials{i} = eegtoolkit.util.Trial(E.session.trials{i}.signal,<span class="keyword">...</span>
+0072                             E.session.trials{i}.label,E.session.trials{i}.samplingRate,E.session.trials{i}.subjectid,E.session.trials{i}.sessionid,E.session.trials{i}.type);
+0073             <span class="keyword">end</span>
+0074             <span class="keyword">if</span> ~isempty(E.preprocessing)
+0075                 <span class="keyword">for</span> i=1:length(E.preprocessing)
+0076                     <span class="keyword">if</span> isa(E.preprocessing{i},<span class="string">'eegtoolkit.preprocessing.Windsorize'</span>)
+0077                         E.preprocessing{i}.subjectids = E.subjectids;
+0078                     <span class="keyword">end</span>
+0079                     trials = E.preprocessing{i}.process(trials);
+0080                 <span class="keyword">end</span>
+0081             <span class="keyword">end</span>
+0082             disp(<span class="string">'feature extraction ...'</span>);
+0083             <span class="keyword">if</span> iscell(E.featextraction)
+0084                 numExtract = length(E.featextraction);
+0085                 <span class="keyword">for</span> i=1:numExtract
+0086                     E.featextraction{i}.trials = trials;
+0087                     E.featextraction{i}.extract;    
+0088                 <span class="keyword">end</span>
+0089                 E.aggregator.featextractors = E.featextraction;
+0090                 E.aggregator.aggregate;
+0091                 instanceSet = E.aggregator.instanceSet;
+0092             <span class="keyword">else</span>
+0093                 E.featextraction.trials = trials;
+0094                 E.featextraction.extract;
+0095                 instanceSet = E.featextraction.getInstanceSet;
+0096             <span class="keyword">end</span>
+0097             <span class="keyword">if</span> ~isempty(E.featselection)
+0098                 E.featselection.originalInstanceSet = instanceSet;
+0099                 disp(<span class="string">'feature selection ...'</span>);
+0100                 E.featselection.compute;
+0101                 E.classification.instanceSet = E.featselection.filteredInstanceSet;
+0102             <span class="keyword">else</span>
+0103                 E.classification.instanceSet = instanceSet;
+0104             <span class="keyword">end</span>
+0105             disp(<span class="string">'evaluating..'</span>);
+0106             <span class="keyword">switch</span> E.evalMethod
+0107                 <span class="keyword">case</span> E.EVAL_METHOD_LOOCV
+0108                     E.leaveOneOutCV();
+0109                 <span class="keyword">case</span> E.EVAL_METHOD_LOSO
+0110                     subjects = unique(E.subjectids);
+0111                     instanceSet = E.classification.instanceSet;
+0112                     <span class="keyword">if</span> isa(E.classification,<span class="string">'eegtoolkit.classification.LIBSVMFast'</span>)
+0113                         instanceSet.K = instanceSet.computeKernel(E.classification.kernel,E.classification.gamma,E.classification.maxlag,E.classification.scaleopt);
+0114                     <span class="keyword">end</span>
+0115                     <span class="keyword">for</span> i=1:length(subjects)
+0116                         fprintf(<span class="string">'leaving subject #%d out\n'</span>, i);
+0117                         <span class="keyword">if</span> isa(E.classification,<span class="string">'eegtoolkit.classification.LIBSVMFast'</span>)
+0118                             E.leaveOneSubjectOutFast(subjects(i), instanceSet);
+0119                         <span class="keyword">else</span>
+0120                             
+0121                             E.leaveOneSubjectOut(subjects(i), instanceSet);
+0122                         <span class="keyword">end</span>
+0123                         
+0124                     <span class="keyword">end</span>
+0125                 <span class="keyword">case</span> E.EVAL_METHOD_LOBO
+0126                     sessions = unique(E.sessionids);
+0127                     instanceSet = E.classification.instanceSet;
+0128                     <span class="keyword">for</span> i=1:length(sessions)
+0129                         fprintf(<span class="string">'leaving session #%d out\n'</span>, i);
+0130                         E.leaveOneSessionOut(sessions(i), instanceSet);
+0131                     <span class="keyword">end</span>
+0132                 <span class="keyword">case</span> E.EVAL_METHOD_SPLIT
+0133                     instanceSet = E.classification.instanceSet;
+0134                     E.splitTest(trainIDx,testIDx,instanceSet);
+0135                 <span class="keyword">case</span> E.EVAL_METHOD_XFOLD_CV
+0136                     instanceSet = E.classification.instanceSet;
+0137                     E.kfoldCrossValidation(instanceSet,numFolds);
+0138                 <span class="keyword">case</span> E.EVAL_METHOD_LOSO_LOBO
+0139                     instanceSet = E.classification.instanceSet;
+0140                     E.leaveOneSubjectOutLeaveOneBlockOut(instanceSet);
+0141                 <span class="keyword">otherwise</span>
+0142                     error (<span class="string">'eval method not set or invalid'</span>);
+0143             <span class="keyword">end</span>
+0144         <span class="keyword">end</span>
+0145         
+0146         <a name="_sub2" href="#_subfunctions" class="code">function itrs = getITR(E)</a>
+0147             <span class="keyword">for</span> i=1:length(E.preprocessing)
+0148                 <span class="keyword">if</span> isa(E.preprocessing{i},<span class="string">'eegtoolkit.preprocessing.SampleSelection'</span>)
+0149                     <span class="comment">%T = time in seconds;</span>
+0150                     T = (E.preprocessing{i}.sampleRange(2)-E.preprocessing{i}.sampleRange(1)+1)/E.preprocessing{i}.samplingRate;
+0151                 <span class="keyword">end</span>
+0152             <span class="keyword">end</span>
+0153             <span class="keyword">if</span> isempty(T)
+0154                 error(<span class="string">'to calculate ITR the SampleSelection preprocessing step must be added to the experiment'</span>);
+0155             <span class="keyword">end</span>
+0156             <span class="keyword">for</span> i=1:length(E.results)
+0157                 itrs(i) = E.results{i}.getITR(T);
+0158             <span class="keyword">end</span>
+0159         <span class="keyword">end</span>
+0160         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(E)</a>
+0161             info = <span class="string">'Average time elapsed for trial:\n'</span>;
+0162             total = 0;
+0163             <span class="keyword">if</span> ~isempty(E.preprocessing)
+0164                 info = strcat(info, <span class="string">'Preprocessing:\n'</span>);
+0165                 <span class="keyword">for</span> i=1:length(E.preprocessing)
+0166                     info = strcat(info, num2str(E.preprocessing{i}.getTime));
+0167                     total = total + E.preprocessing{i}.getTime;
+0168                     info = strcat(info, <span class="string">'\n'</span>);
+0169                 <span class="keyword">end</span>
+0170             <span class="keyword">end</span>
+0171             <span class="keyword">if</span> ~isempty(E.featextraction)
+0172                 info = strcat(info, <span class="string">'Feature Extraction:\n'</span>);
+0173                 <span class="keyword">if</span> ~iscell(E.featextraction)
+0174                     info = strcat(info, num2str(E.featextraction.getTime));
+0175                     total = total + E.featextraction.getTime;
+0176                     info = strcat(info, <span class="string">'\n'</span>);
+0177                 <span class="keyword">else</span>
+0178                     <span class="keyword">for</span> i=1:length(E.featextraction)
+0179                         info = strcat(info, num2str(E.featextraction{i}.getTime));
+0180                         total = total + E.featextraction{i}.getTime;
+0181                         info = strcat(info,<span class="string">'\n'</span>);
+0182                     <span class="keyword">end</span>
+0183                 <span class="keyword">end</span>
+0184             <span class="keyword">end</span>
+0185             <span class="keyword">if</span> ~isempty(E.aggregator)
+0186                 info = strcat(info, <span class="string">'Aggregation:\n'</span>);
+0187                 info = strcat(info, num2str(E.aggregator.getTime));
+0188                 total = total + E.aggregator.getTime;
+0189                 info = strcat(info, <span class="string">'\n'</span>);
+0190             <span class="keyword">end</span>
+0191             <span class="keyword">if</span> ~isempty(E.featselection)
+0192                 info = strcat(info, <span class="string">'FeatureSelection:\n'</span>);
+0193                 info = strcat(info, num2str(E.featselection.getTime));
+0194                 total = total + E.featselection.getTime;
+0195                 info = strcat(info, <span class="string">'\n'</span>);
+0196             <span class="keyword">end</span>
+0197             <span class="keyword">if</span> ~isempty(E.classification)
+0198                 info = strcat(info, <span class="string">'Classification (Prediction):\n'</span>);
+0199                 info = strcat(info, num2str(E.classification.getTime));
+0200                 total = total + E.classification.getTime;
+0201                 info = strcat(info, <span class="string">'\n'</span>);
+0202             <span class="keyword">end</span>
+0203             info = strcat(info, <span class="string">'Total:\n'</span>);
+0204             info = strcat(info, num2str(total));
+0205             time = sprintf(info);
+0206         <span class="keyword">end</span>
+0207         
+0208         <a name="_sub4" href="#_subfunctions" class="code">function info = getExperimentInfo(E)</a>
+0209             <span class="comment">% Prints the configuration info of the experiment</span>
+0210             info = <span class="string">'Experiment Configuration:\n'</span>;
+0211             <span class="keyword">if</span> ~isempty(E.preprocessing)
+0212                 <span class="keyword">for</span> i=1:length(E.preprocessing)
+0213                     info = strcat(info, E.preprocessing{i}.getConfigInfo);
+0214                     info = strcat(info,<span class="string">'\n'</span>);
+0215                 <span class="keyword">end</span>
+0216             <span class="keyword">end</span>
+0217             <span class="keyword">if</span> ~isempty(E.featextraction)
+0218                 <span class="keyword">if</span> ~iscell(E.featextraction)
+0219                     info = strcat(info, E.featextraction.getConfigInfo);
+0220                     info = strcat(info,<span class="string">'\n'</span>);
+0221                 <span class="keyword">else</span>
+0222                     <span class="keyword">for</span> i=1:length(E.featextraction)
+0223                         info = strcat(info, E.featextraction{i}.getConfigInfo);
+0224                         info = strcat(info,<span class="string">'\n'</span>);
+0225                     <span class="keyword">end</span>
+0226                 <span class="keyword">end</span>
+0227             <span class="keyword">end</span>
+0228             <span class="keyword">if</span> ~isempty(E.aggregator)
+0229                 info = strcat(info, E.aggregator.getConfigInfo);
+0230                 info = strcat(info, <span class="string">'\n'</span>);
+0231             <span class="keyword">end</span>
+0232             <span class="keyword">if</span> ~isempty(E.featselection)
+0233                 info = strcat(info, E.featselection.getConfigInfo);
+0234                 info = strcat(info, <span class="string">'\n'</span>);
+0235             <span class="keyword">end</span>
+0236             <span class="keyword">if</span> ~isempty(E.classification)
+0237                 info = strcat(info, E.classification.getConfigInfo);
+0238                 info = strcat(info, <span class="string">'\n'</span>);
+0239             <span class="keyword">end</span>
+0240             info = sprintf(info);
+0241         <span class="keyword">end</span>
+0242         
+0243     <span class="keyword">end</span>
+0244     
+0245     methods (Access = private)
+0246         
+0247         <a name="_sub5" href="#_subfunctions" class="code">function E = checkCompatibility(E)</a>
+0248             <span class="keyword">if</span> iscell(E.featextraction)
+0249                 <span class="keyword">if</span> isempty(E.aggregator)
+0250                     error (<span class="string">'Provided many feature extractors but not an Aggregator'</span>);
+0251                 <span class="keyword">end</span>
+0252             <span class="keyword">end</span>
+0253             <span class="keyword">if</span> isa(E.classification,<span class="string">'eegtoolkit.classification.LIBSVMFast'</span>) &amp;&amp; E.evalMethod == 0
+0254                 error(<span class="string">'LIBSVMFast not supported for LOOCV eval method'</span>);
+0255             <span class="keyword">end</span>
+0256         <span class="keyword">end</span>
+0257             
+0258         <a name="_sub6" href="#_subfunctions" class="code">function E = leaveOneOutCV(E)</a>
+0259             <span class="comment">%leave one out cross validation</span>
+0260             instanceSet = E.classification.instanceSet;
+0261             numInstances = instanceSet.getNumInstances;
+0262             outputLabels = zeros(numInstances,1);
+0263             outputScores = zeros(numInstances,1);
+0264             outputRanking = zeros(numInstances, instanceSet.getNumLabels);
+0265             h = waitbar(0,<span class="string">'Cross-validating..'</span>);
+0266             <span class="keyword">for</span> i=1:numInstances
+0267                 waitbar(i/numInstances,h,sprintf(<span class="string">'Cross-validating fold: %d/%d'</span>, i, numInstances));
+0268                 <span class="comment">%train the classifier without 1 instance</span>
+0269                 E.classification.instanceSet = instanceSet.removeInstancesWithIndices(i);
+0270                 E.classification.build();
+0271                 <span class="comment">%predict the label of the omitted instance</span>
+0272                 [outputLabels(i,1), outputScores(i,1), outputRanking(i,:)] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(i));
+0273             <span class="keyword">end</span>
+0274             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDataset, outputLabels, outputScores, outputRanking);
+0275             E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0276             close(h);
+0277         <span class="keyword">end</span>
+0278         
+0279         <a name="_sub7" href="#_subfunctions" class="code">function E = kfoldCrossValidation(E,instanceSet,numFolds)</a>
+0280             numInstances = instanceSet.getNumInstances;
+0281             indices = crossvalind(<span class="string">'Kfold'</span>, numInstances, numFolds);
+0282             outputLabels = zeros(numInstances,1);
+0283             outputScores = zeros(numInstances,1);
+0284             outputRanking = zeros(numInstances,instanceSet.getNumLabels);
+0285             h = waitbar(0,<span class="string">'Cross-validating..'</span>);
+0286             <span class="keyword">for</span> i=1:numFolds
+0287                 waitbar(i/numFolds,h,sprintf(<span class="string">'Cross-validating fold: %d/%d'</span>,i,numFolds));
+0288                 testSet = find(indices==i);
+0289                 E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testSet);
+0290                 E.classification.build();
+0291                 
+0292                 [outputLabels(testSet,1), outputScores(testSet,1), outputRanking(testSet,:)] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testSet));
+0293             <span class="keyword">end</span>
+0294             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDataset, outputLabels, outputScores, outputRanking);
+0295             E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0296             close(h);
+0297         <span class="keyword">end</span>
+0298         
+0299         <a name="_sub8" href="#_subfunctions" class="code">function resultSet = leaveOneSubjectOut(E, subjectid, instanceSet)</a>
+0300             testingset = find(E.subjectids == subjectid);
+0301             E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+0302             E.classification.build();
+0303             [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+0304             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+0305             E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0306         <span class="keyword">end</span>
+0307         
+0308                 
+0309         <a name="_sub9" href="#_subfunctions" class="code">function resultSet = leaveOneSubjectOutLeaveOneBlockOut(E, instanceSet)</a>
+0310             subjects = unique(E.subjectids);
+0311             sessions = unique(E.sessionids);
+0312             <span class="keyword">for</span> i=1:length(subjects)
+0313                 numInstancesForSubject = sum(E.subjectids==subjects(i));
+0314                 outputLabels = zeros(numInstancesForSubject,1);
+0315                 outputScores = zeros(numInstancesForSubject,1);
+0316                 outputRanking = zeros(numInstancesForSubject,instanceSet.getNumLabels());
+0317                 <span class="keyword">for</span> j=1:length(sessions)
+0318 <span class="comment">%                     tempResults{j} = E.leaveOneSessionOut(sessions(j),tempInstanceSet);</span>
+0319                     sessionidsSubset = E.sessionids(E.subjectids==subjects(i));
+0320                     testIndices = sessionidsSubset==sessions(j);
+0321                     numInstancesForSession = sum(E.sessionids==sessions(j)&amp;E.subjectids==subjects(i));
+0322                     testingset = find(E.sessionids==sessions(j)&amp;E.subjectids==subjects(i));
+0323                     nottrainset = find(E.sessionids==sessions(j)|E.subjectids~=subjects(i));
+0324                     E.classification.instanceSet = instanceSet.removeInstancesWithIndices(nottrainset);
+0325                     E.classification.build();
+0326                     [outputLabels(testIndices,:), outputScores(testIndices,:), outputRanking(testIndices,:)] = <span class="keyword">...</span>
+0327                         E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+0328                     
+0329                 <span class="keyword">end</span>
+0330                 sIndices = find(E.subjectids==subjects(i));
+0331                 resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(sIndices),outputLabels,outputScores,outputRanking);
+0332                 E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0333                 <span class="comment">%merge the results</span>
+0334             <span class="keyword">end</span>
+0335         <span class="keyword">end</span>
+0336         
+0337         
+0338         <a name="_sub10" href="#_subfunctions" class="code">function resultSet = leaveOneSessionOut(E, sessionId, instanceSet)</a>
+0339             testingset = find(E.sessionids == sessionId);
+0340             trainset = find(E.sessionids ~= sessionId);
+0341             E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+0342             E.classification.build();
+0343             [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+0344             [trainoutputLabels, trainoutputScores, trainoutputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(trainset));
+0345             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+0346             trainresultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(trainset), trainoutputLabels, trainoutputScores, trainoutputRanking);
+0347             E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0348             E.trainresults{length(E.trainresults)+1} = eegtoolkit.experiment.ResultEvaluator(trainresultSet);
+0349         <span class="keyword">end</span>
+0350         
+0351         <a name="_sub11" href="#_subfunctions" class="code">function resultSet = leaveOneSubjectOutFast(E, subjectid, instanceSet)</a>
+0352             testingset = E.subjectids == subjectid;
+0353             E.classification.Ktrain = instanceSet.getTrainKernel(~testingset);
+0354             E.classification.Ktest = instanceSet.getTestKernel(~testingset,testingset);
+0355             testingset = find(E.subjectids == subjectid);
+0356             E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+0357             E.classification.build();
+0358             [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance();
+0359             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+0360             resultEvaluator = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0361             resultEvaluator.subjectid = E.subjectids(E.subjectids==subjectid);
+0362             resultEvaluator.sessionid = E.session.sessionids(E.subjectids==subjectid);
+0363             E.results{length(E.results)+1} = resultEvaluator;
+0364         <span class="keyword">end</span>
+0365 
+0366         <a name="_sub12" href="#_subfunctions" class="code">function resultSet = splitTest(E,trainIDx,testIDx, instanceSet)</a>
+0367             E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testIDx);
+0368             E.classification.build();
+0369             [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testIDx));
+0370             resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testIDx), outputLabels, outputScores, outputRanking);
+0371             resultEvaluator = eegtoolkit.experiment.ResultEvaluator(resultSet);
+0372             E.results{length(E.results) + 1} = resultEvaluator;
+0373         <span class="keyword">end</span>
+0374         
+0375 
+0376                 
+0377             
+0378     <span class="keyword">end</span>
+0379     
+0380 <span class="keyword">end</span>
+0381</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.m b/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.m
new file mode 100644
index 0000000..9b28677
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/Experimenter.m
@@ -0,0 +1,381 @@
+% EXPERIMENTER class
+% Wraps all the necessary objects for performing an experiment. 
+%Before running an experiment all the required properties must be set.
+% Required:
+% - session
+% - featextraction
+% - evalMethod
+% - classification
+% Optional:
+% - featselection
+% - aggregator
+% - preprocessing
+%
+% to run the experiment execute the "run()" method.
+% Example:
+% experiment = eegtoolkit.experiment.Experimenter;
+% experiment.session = eegtoolkit.util.Session;
+% experiment.session.loadSubject(1);
+% experiment.transformer = eegtoolkit.featextraction.PWelch;
+% experiment.extractor = eegtoolkit.featselection.FEAST;
+% experiment.classification = eegtoolkit.classification.LIBSVM;
+% experiment.evalMethod = experiment.evalMethod.EVAL_METHOD_LOSO;
+% experiment.run;
+% results = experiment.results;
+% confmatrix = results{1}.getConfusionMatrix;
+classdef Experimenter < handle
+    properties (Constant)
+        EVAL_METHOD_LOOCV = 0; % Leave One Out Cross-Validation
+        EVAL_METHOD_LOSO = 1; % Leave One Subject Out
+        EVAL_METHOD_LOBO = 2;
+        EVAL_METHOD_SPLIT = 3;
+        EVAL_METHOD_XFOLD_CV = 4;
+        EVAL_METHOD_LOSO_LOBO = 5;
+    end
+    
+    properties (Access = public)
+        session; % The Session object. Trials must be loaded before run() is executed
+        preprocessing;
+        featextraction; % A transformer object
+        aggregator;
+        featselection; % An extractor object
+        evalMethod; % The evaluation method
+        classification; % A classifier object
+        results; % A cell array containing objects of the 'ResultEvaluator' class.
+        trainresults;
+        subjectids;
+        sessionids;
+    end
+    
+    methods
+        function E = Experimenter(evalMethod)
+            if nargin > 0
+                E.evalMethod = evalMethod;
+            else E.evalMethod = 0;
+            end
+            E.results = {};
+        end
+        function E = run(E,varargin)
+            if(length(varargin)==1)
+                numFolds = varargin{1};
+            elseif(length(varargin)==2)
+                trainIDx = varargin{1};
+                testIDx = varargin{2};
+            end
+            % Runs an experiment
+            E.checkCompatibility;
+            E.subjectids = E.session.subjectids;
+            E.sessionids = E.session.sessionids;
+            trials = {};
+            for i=1:length(E.session.trials)
+                trials{i} = eegtoolkit.util.Trial(E.session.trials{i}.signal,...
+                            E.session.trials{i}.label,E.session.trials{i}.samplingRate,E.session.trials{i}.subjectid,E.session.trials{i}.sessionid,E.session.trials{i}.type);
+            end
+            if ~isempty(E.preprocessing)
+                for i=1:length(E.preprocessing)
+                    if isa(E.preprocessing{i},'eegtoolkit.preprocessing.Windsorize')
+                        E.preprocessing{i}.subjectids = E.subjectids;
+                    end
+                    trials = E.preprocessing{i}.process(trials);
+                end
+            end
+            disp('feature extraction ...');
+            if iscell(E.featextraction)
+                numExtract = length(E.featextraction);
+                for i=1:numExtract
+                    E.featextraction{i}.trials = trials;
+                    E.featextraction{i}.extract;    
+                end
+                E.aggregator.featextractors = E.featextraction;
+                E.aggregator.aggregate;
+                instanceSet = E.aggregator.instanceSet;
+            else
+                E.featextraction.trials = trials;
+                E.featextraction.extract;
+                instanceSet = E.featextraction.getInstanceSet;
+            end
+            if ~isempty(E.featselection)
+                E.featselection.originalInstanceSet = instanceSet;
+                disp('feature selection ...');
+                E.featselection.compute;
+                E.classification.instanceSet = E.featselection.filteredInstanceSet;
+            else
+                E.classification.instanceSet = instanceSet;
+            end
+            disp('evaluating..');
+            switch E.evalMethod
+                case E.EVAL_METHOD_LOOCV
+                    E.leaveOneOutCV();
+                case E.EVAL_METHOD_LOSO
+                    subjects = unique(E.subjectids);
+                    instanceSet = E.classification.instanceSet;
+                    if isa(E.classification,'eegtoolkit.classification.LIBSVMFast')
+                        instanceSet.K = instanceSet.computeKernel(E.classification.kernel,E.classification.gamma,E.classification.maxlag,E.classification.scaleopt);
+                    end
+                    for i=1:length(subjects)
+                        fprintf('leaving subject #%d out\n', i);
+                        if isa(E.classification,'eegtoolkit.classification.LIBSVMFast')
+                            E.leaveOneSubjectOutFast(subjects(i), instanceSet);
+                        else
+                            
+                            E.leaveOneSubjectOut(subjects(i), instanceSet);
+                        end
+                        
+                    end
+                case E.EVAL_METHOD_LOBO
+                    sessions = unique(E.sessionids);
+                    instanceSet = E.classification.instanceSet;
+                    for i=1:length(sessions)
+                        fprintf('leaving session #%d out\n', i);
+                        E.leaveOneSessionOut(sessions(i), instanceSet);
+                    end
+                case E.EVAL_METHOD_SPLIT
+                    instanceSet = E.classification.instanceSet;
+                    E.splitTest(trainIDx,testIDx,instanceSet);
+                case E.EVAL_METHOD_XFOLD_CV
+                    instanceSet = E.classification.instanceSet;
+                    E.kfoldCrossValidation(instanceSet,numFolds);
+                case E.EVAL_METHOD_LOSO_LOBO
+                    instanceSet = E.classification.instanceSet;
+                    E.leaveOneSubjectOutLeaveOneBlockOut(instanceSet);
+                otherwise
+                    error ('eval method not set or invalid');
+            end
+        end
+        
+        function itrs = getITR(E)
+            for i=1:length(E.preprocessing)
+                if isa(E.preprocessing{i},'eegtoolkit.preprocessing.SampleSelection')
+                    %T = time in seconds;
+                    T = (E.preprocessing{i}.sampleRange(2)-E.preprocessing{i}.sampleRange(1)+1)/E.preprocessing{i}.samplingRate;
+                end
+            end
+            if isempty(T)
+                error('to calculate ITR the SampleSelection preprocessing step must be added to the experiment');
+            end
+            for i=1:length(E.results)
+                itrs(i) = E.results{i}.getITR(T);
+            end
+        end
+        function time = getTime(E)
+            info = 'Average time elapsed for trial:\n';
+            total = 0;
+            if ~isempty(E.preprocessing)
+                info = strcat(info, 'Preprocessing:\n');
+                for i=1:length(E.preprocessing)
+                    info = strcat(info, num2str(E.preprocessing{i}.getTime));
+                    total = total + E.preprocessing{i}.getTime;
+                    info = strcat(info, '\n');
+                end
+            end
+            if ~isempty(E.featextraction)
+                info = strcat(info, 'Feature Extraction:\n');
+                if ~iscell(E.featextraction)
+                    info = strcat(info, num2str(E.featextraction.getTime));
+                    total = total + E.featextraction.getTime;
+                    info = strcat(info, '\n');
+                else
+                    for i=1:length(E.featextraction)
+                        info = strcat(info, num2str(E.featextraction{i}.getTime));
+                        total = total + E.featextraction{i}.getTime;
+                        info = strcat(info,'\n');
+                    end
+                end
+            end
+            if ~isempty(E.aggregator)
+                info = strcat(info, 'Aggregation:\n');
+                info = strcat(info, num2str(E.aggregator.getTime));
+                total = total + E.aggregator.getTime;
+                info = strcat(info, '\n');
+            end
+            if ~isempty(E.featselection)
+                info = strcat(info, 'FeatureSelection:\n');
+                info = strcat(info, num2str(E.featselection.getTime));
+                total = total + E.featselection.getTime;
+                info = strcat(info, '\n');
+            end
+            if ~isempty(E.classification)
+                info = strcat(info, 'Classification (Prediction):\n');
+                info = strcat(info, num2str(E.classification.getTime));
+                total = total + E.classification.getTime;
+                info = strcat(info, '\n');
+            end
+            info = strcat(info, 'Total:\n');
+            info = strcat(info, num2str(total));
+            time = sprintf(info);
+        end
+        
+        function info = getExperimentInfo(E)
+            % Prints the configuration info of the experiment
+            info = 'Experiment Configuration:\n';
+            if ~isempty(E.preprocessing)
+                for i=1:length(E.preprocessing)
+                    info = strcat(info, E.preprocessing{i}.getConfigInfo);
+                    info = strcat(info,'\n');
+                end
+            end
+            if ~isempty(E.featextraction)
+                if ~iscell(E.featextraction)
+                    info = strcat(info, E.featextraction.getConfigInfo);
+                    info = strcat(info,'\n');
+                else
+                    for i=1:length(E.featextraction)
+                        info = strcat(info, E.featextraction{i}.getConfigInfo);
+                        info = strcat(info,'\n');
+                    end
+                end
+            end
+            if ~isempty(E.aggregator)
+                info = strcat(info, E.aggregator.getConfigInfo);
+                info = strcat(info, '\n');
+            end
+            if ~isempty(E.featselection)
+                info = strcat(info, E.featselection.getConfigInfo);
+                info = strcat(info, '\n');
+            end
+            if ~isempty(E.classification)
+                info = strcat(info, E.classification.getConfigInfo);
+                info = strcat(info, '\n');
+            end
+            info = sprintf(info);
+        end
+        
+    end
+    
+    methods (Access = private)
+        
+        function E = checkCompatibility(E)
+            if iscell(E.featextraction)
+                if isempty(E.aggregator)
+                    error ('Provided many feature extractors but not an Aggregator');
+                end
+            end
+            if isa(E.classification,'eegtoolkit.classification.LIBSVMFast') && E.evalMethod == 0
+                error('LIBSVMFast not supported for LOOCV eval method');
+            end
+        end
+            
+        function E = leaveOneOutCV(E)
+            %leave one out cross validation
+            instanceSet = E.classification.instanceSet;
+            numInstances = instanceSet.getNumInstances;
+            outputLabels = zeros(numInstances,1);
+            outputScores = zeros(numInstances,1);
+            outputRanking = zeros(numInstances, instanceSet.getNumLabels);
+            h = waitbar(0,'Cross-validating..');
+            for i=1:numInstances
+                waitbar(i/numInstances,h,sprintf('Cross-validating fold: %d/%d', i, numInstances));
+                %train the classifier without 1 instance
+                E.classification.instanceSet = instanceSet.removeInstancesWithIndices(i);
+                E.classification.build();
+                %predict the label of the omitted instance
+                [outputLabels(i,1), outputScores(i,1), outputRanking(i,:)] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(i));
+            end
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDataset, outputLabels, outputScores, outputRanking);
+            E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+            close(h);
+        end
+        
+        function E = kfoldCrossValidation(E,instanceSet,numFolds)
+            numInstances = instanceSet.getNumInstances;
+            indices = crossvalind('Kfold', numInstances, numFolds);
+            outputLabels = zeros(numInstances,1);
+            outputScores = zeros(numInstances,1);
+            outputRanking = zeros(numInstances,instanceSet.getNumLabels);
+            h = waitbar(0,'Cross-validating..');
+            for i=1:numFolds
+                waitbar(i/numFolds,h,sprintf('Cross-validating fold: %d/%d',i,numFolds));
+                testSet = find(indices==i);
+                E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testSet);
+                E.classification.build();
+                
+                [outputLabels(testSet,1), outputScores(testSet,1), outputRanking(testSet,:)] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testSet));
+            end
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDataset, outputLabels, outputScores, outputRanking);
+            E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+            close(h);
+        end
+        
+        function resultSet = leaveOneSubjectOut(E, subjectid, instanceSet)
+            testingset = find(E.subjectids == subjectid);
+            E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+            E.classification.build();
+            [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+            E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+        end
+        
+                
+        function resultSet = leaveOneSubjectOutLeaveOneBlockOut(E, instanceSet)
+            subjects = unique(E.subjectids);
+            sessions = unique(E.sessionids);
+            for i=1:length(subjects)
+                numInstancesForSubject = sum(E.subjectids==subjects(i));
+                outputLabels = zeros(numInstancesForSubject,1);
+                outputScores = zeros(numInstancesForSubject,1);
+                outputRanking = zeros(numInstancesForSubject,instanceSet.getNumLabels());
+                for j=1:length(sessions)
+%                     tempResults{j} = E.leaveOneSessionOut(sessions(j),tempInstanceSet);
+                    sessionidsSubset = E.sessionids(E.subjectids==subjects(i));
+                    testIndices = sessionidsSubset==sessions(j);
+                    numInstancesForSession = sum(E.sessionids==sessions(j)&E.subjectids==subjects(i));
+                    testingset = find(E.sessionids==sessions(j)&E.subjectids==subjects(i));
+                    nottrainset = find(E.sessionids==sessions(j)|E.subjectids~=subjects(i));
+                    E.classification.instanceSet = instanceSet.removeInstancesWithIndices(nottrainset);
+                    E.classification.build();
+                    [outputLabels(testIndices,:), outputScores(testIndices,:), outputRanking(testIndices,:)] = ...
+                        E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+                    
+                end
+                sIndices = find(E.subjectids==subjects(i));
+                resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(sIndices),outputLabels,outputScores,outputRanking);
+                E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+                %merge the results
+            end
+        end
+        
+        
+        function resultSet = leaveOneSessionOut(E, sessionId, instanceSet)
+            testingset = find(E.sessionids == sessionId);
+            trainset = find(E.sessionids ~= sessionId);
+            E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+            E.classification.build();
+            [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testingset));
+            [trainoutputLabels, trainoutputScores, trainoutputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(trainset));
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+            trainresultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(trainset), trainoutputLabels, trainoutputScores, trainoutputRanking);
+            E.results{length(E.results)+1} = eegtoolkit.experiment.ResultEvaluator(resultSet);
+            E.trainresults{length(E.trainresults)+1} = eegtoolkit.experiment.ResultEvaluator(trainresultSet);
+        end
+        
+        function resultSet = leaveOneSubjectOutFast(E, subjectid, instanceSet)
+            testingset = E.subjectids == subjectid;
+            E.classification.Ktrain = instanceSet.getTrainKernel(~testingset);
+            E.classification.Ktest = instanceSet.getTestKernel(~testingset,testingset);
+            testingset = find(E.subjectids == subjectid);
+            E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testingset);
+            E.classification.build();
+            [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance();
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testingset), outputLabels, outputScores, outputRanking);
+            resultEvaluator = eegtoolkit.experiment.ResultEvaluator(resultSet);
+            resultEvaluator.subjectid = E.subjectids(E.subjectids==subjectid);
+            resultEvaluator.sessionid = E.session.sessionids(E.subjectids==subjectid);
+            E.results{length(E.results)+1} = resultEvaluator;
+        end
+
+        function resultSet = splitTest(E,trainIDx,testIDx, instanceSet)
+            E.classification.instanceSet = instanceSet.removeInstancesWithIndices(testIDx);
+            E.classification.build();
+            [outputLabels, outputScores, outputRanking] = E.classification.classifyInstance(instanceSet.getInstancesWithIndices(testIDx));
+            resultSet = eegtoolkit.util.ResultSet(instanceSet.getDatasetWithIndices(testIDx), outputLabels, outputScores, outputRanking);
+            resultEvaluator = eegtoolkit.experiment.ResultEvaluator(resultSet);
+            E.results{length(E.results) + 1} = resultEvaluator;
+        end
+        
+
+                
+            
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/graph.dot b/doc/+eegtoolkit/+experiment/@Experimenter/graph.dot
new file mode 100644
index 0000000..c2a7d3c
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Experimenter -> Experimenter;
+
+  Experimenter [URL="Experimenter.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/graph.html b/doc/+eegtoolkit/+experiment/@Experimenter/graph.html
new file mode 100644
index 0000000..13301f1
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+experiment/@Experimenter</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+experiment/@Experimenter">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+experiment/@Experimenter">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@Experimenter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+experiment/@Experimenter</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+experiment/@Experimenter" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Experimenter.html" title="Experimenter" alt="" coords="163,29,159,22,148,15,130,10,108,7,84,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,84,53,108,52,130,49,148,43,159,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/graph.map b/doc/+eegtoolkit/+experiment/@Experimenter/graph.map
new file mode 100644
index 0000000..1e7afc3
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="Experimenter.html" title="Experimenter" alt="" coords="163,29,159,22,148,15,130,10,108,7,84,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,84,53,108,52,130,49,148,43,159,37">
diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/graph.png b/doc/+eegtoolkit/+experiment/@Experimenter/graph.png
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diff --git a/doc/+eegtoolkit/+experiment/@Experimenter/index.html b/doc/+eegtoolkit/+experiment/@Experimenter/index.html
new file mode 100644
index 0000000..7bbd635
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@Experimenter/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+experiment/@Experimenter</title>
+  <meta name="keywords" content="./+eegtoolkit/+experiment/@Experimenter">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+experiment/@Experimenter">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@Experimenter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+experiment/@Experimenter</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Experimenter.html">Experimenter</a></td><td>EXPERIMENTER class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.html b/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.html
new file mode 100644
index 0000000..abf7cae
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.html
@@ -0,0 +1,136 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ResultEvaluator</title>
+  <meta name="keywords" content="ResultEvaluator">
+  <meta name="description" content="RESULTEVALUATOR class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+experiment</a> &gt; <a href="#">@ResultEvaluator</a> &gt; ResultEvaluator.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@ResultEvaluator&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ResultEvaluator
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>RESULTEVALUATOR class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> RESULTEVALUATOR class
+ Parses the results of an experiment and calculates various metrics</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ResultEvaluator.html" class="code" title="">ResultEvaluator</a>	RESULTEVALUATOR class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ResultEvaluator.html" class="code" title="">ResultEvaluator</a>	RESULTEVALUATOR class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function RE = ResultEvaluator(resultSet)</a></li><li><a href="#_sub2" class="code">function acc = getAccuracy(RE)</a></li><li><a href="#_sub3" class="code">function confusionMatrix = getConfusionMatrix(RE)</a></li><li><a href="#_sub4" class="code">function acc = getAccuracyForSession(RE,session)</a></li><li><a href="#_sub5" class="code">function accuracies = getAccuracyBySession(RE)</a></li><li><a href="#_sub6" class="code">function accuracies = getAccuracyByLabel(RE)</a></li><li><a href="#_sub7" class="code">function ITR = getITR(RE,T)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ResultEvaluator.m">ResultEvaluator.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% RESULTEVALUATOR class</span>
+0002 <span class="comment">% Parses the results of an experiment and calculates various metrics</span>
+0003 classdef  <a href="ResultEvaluator.html" class="code" title="">ResultEvaluator</a> &lt; handle
+0004     properties
+0005         resultSet; <span class="comment">% A 'ResultSet' object containing the results of an experiment</span>
+0006         subjectid; <span class="comment">% The subject ids corresponding</span>
+0007         sessionid;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods 
+0011         <a name="_sub0" href="#_subfunctions" class="code">function RE = ResultEvaluator(resultSet)</a>
+0012             <span class="keyword">if</span> nargin &gt; 0
+0013                 RE.resultSet = resultSet;
+0014             <span class="keyword">end</span>
+0015         <span class="keyword">end</span>
+0016         
+0017         <a name="_sub1" href="#_subfunctions" class="code">function acc = getAccuracy(RE)</a>
+0018             conf = RE.resultSet.confusionMatrix;
+0019             acc = sum(diag(conf))/sum(sum(conf))*100;
+0020         <span class="keyword">end</span>
+0021         
+0022         <a name="_sub2" href="#_subfunctions" class="code">function confusionMatrix = getConfusionMatrix(RE)</a>
+0023             <span class="comment">%Returns the confusion matrix with labels as the last row</span>
+0024             <span class="comment">%if you want the confusion matrix without labels then</span>
+0025             <span class="comment">%access the confusionMatrix property of the resultSet directly</span>
+0026             labels = unique(RE.resultSet.getLabels);
+0027             confusionMatrix = horzcat(RE.resultSet.confusionMatrix, labels);
+0028         <span class="keyword">end</span>
+0029         
+0030         <a name="_sub3" href="#_subfunctions" class="code">function acc = getAccuracyForSession(RE,session)</a>
+0031             conf = RE.resultSet.subset(RE.sessionid==session).confusionMatrix;
+0032             acc = sum(diag(conf))/sum(sum(conf))*100;
+0033         <span class="keyword">end</span>
+0034         
+0035         <a name="_sub4" href="#_subfunctions" class="code">function accuracies = getAccuracyBySession(RE)</a>
+0036             unsessions = unique(RE.sessionid);
+0037             <span class="keyword">for</span> i=1:length(unsessions)
+0038                 accuracies(i) = RE.getAccuracyForSession(unsessions(i));
+0039             <span class="keyword">end</span>
+0040         <span class="keyword">end</span>
+0041         
+0042         <a name="_sub5" href="#_subfunctions" class="code">function accuracies = getAccuracyByLabel(RE)</a>
+0043             [rows,~] = size(RE.resultSet.confusionMatrix);
+0044             <span class="keyword">for</span> i=1:rows
+0045                 accuracies(i) = RE.resultSet.confusionMatrix(i,i)/sum(RE.resultSet.confusionMatrix(i,:))*100;
+0046             <span class="keyword">end</span>
+0047         <span class="keyword">end</span>
+0048         
+0049         
+0050         <a name="_sub6" href="#_subfunctions" class="code">function ITR = getITR(RE,T)</a>
+0051             P = RE.getAccuracy/100;
+0052             M = RE.resultSet.getNumLabels;
+0053 <span class="comment">%             fprintf('T = %f',T);</span>
+0054 <span class="comment">%             fprintf('P = %f',P);</span>
+0055 <span class="comment">%             fprintf('M = %f',M);</span>
+0056 <span class="comment">%             fprintf('\n');</span>
+0057             ITR = (log2(M) + P*log2(P)+(1-P)*log2((1-P)/(M-1)))/T;
+0058         <span class="keyword">end</span>
+0059         
+0060 <span class="comment">%         function TP = getNumTruePositives(RE)</span>
+0061 <span class="comment">%             conf = RE.resultSet.confusionMatrix;</span>
+0062 <span class="comment">%             TP = diag(conf)';</span>
+0063 <span class="comment">%         end</span>
+0064 <span class="comment">%</span>
+0065 <span class="comment">%         function TN = getNumTrueNegatives(RE)</span>
+0066 <span class="comment">%             numInstances = RE.resultSet.getNumInstances;</span>
+0067 <span class="comment">%             FN = RE.getNumFalseNegatives;</span>
+0068 <span class="comment">%             TP = RE.getNumTruePositives;</span>
+0069 <span class="comment">%             FP = RE.getNumFalsePositives;</span>
+0070 <span class="comment">%             TN = numInstances - FN - TP - FP;</span>
+0071 <span class="comment">%         end</span>
+0072 <span class="comment">%</span>
+0073 <span class="comment">%         function FP = getNumFalsePositives(RE)</span>
+0074 <span class="comment">%             conf = RE.resultSet.confusionMatrix;</span>
+0075 <span class="comment">%             FP = sum(conf') - diag(conf)';</span>
+0076 <span class="comment">%         end</span>
+0077 <span class="comment">%</span>
+0078 <span class="comment">%         function FN = getNumFalseNegatives(RE)</span>
+0079 <span class="comment">%             conf = RE.resultSet.confusionMatrix;</span>
+0080 <span class="comment">%             FN = sum(conf) - diag(conf)';</span>
+0081 <span class="comment">%         end</span>
+0082         
+0083     <span class="keyword">end</span>
+0084 <span class="keyword">end</span>
+0085</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.m b/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.m
new file mode 100644
index 0000000..95999bd
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@ResultEvaluator/ResultEvaluator.m
@@ -0,0 +1,85 @@
+% RESULTEVALUATOR class
+% Parses the results of an experiment and calculates various metrics
+classdef  ResultEvaluator < handle
+    properties
+        resultSet; % A 'ResultSet' object containing the results of an experiment
+        subjectid; % The subject ids corresponding
+        sessionid;
+    end
+    
+    methods 
+        function RE = ResultEvaluator(resultSet)
+            if nargin > 0
+                RE.resultSet = resultSet;
+            end
+        end
+        
+        function acc = getAccuracy(RE)
+            conf = RE.resultSet.confusionMatrix;
+            acc = sum(diag(conf))/sum(sum(conf))*100;
+        end
+        
+        function confusionMatrix = getConfusionMatrix(RE)
+            %Returns the confusion matrix with labels as the last row
+            %if you want the confusion matrix without labels then
+            %access the confusionMatrix property of the resultSet directly
+            labels = unique(RE.resultSet.getLabels);
+            confusionMatrix = horzcat(RE.resultSet.confusionMatrix, labels);
+        end
+        
+        function acc = getAccuracyForSession(RE,session)
+            conf = RE.resultSet.subset(RE.sessionid==session).confusionMatrix;
+            acc = sum(diag(conf))/sum(sum(conf))*100;
+        end
+        
+        function accuracies = getAccuracyBySession(RE)
+            unsessions = unique(RE.sessionid);
+            for i=1:length(unsessions)
+                accuracies(i) = RE.getAccuracyForSession(unsessions(i));
+            end
+        end
+        
+        function accuracies = getAccuracyByLabel(RE)
+            [rows,~] = size(RE.resultSet.confusionMatrix);
+            for i=1:rows
+                accuracies(i) = RE.resultSet.confusionMatrix(i,i)/sum(RE.resultSet.confusionMatrix(i,:))*100;
+            end
+        end
+        
+        
+        function ITR = getITR(RE,T)
+            P = RE.getAccuracy/100;
+            M = RE.resultSet.getNumLabels;
+%             fprintf('T = %f',T);
+%             fprintf('P = %f',P);
+%             fprintf('M = %f',M);
+%             fprintf('\n');
+            ITR = (log2(M) + P*log2(P)+(1-P)*log2((1-P)/(M-1)))/T;
+        end
+        
+%         function TP = getNumTruePositives(RE)
+%             conf = RE.resultSet.confusionMatrix;
+%             TP = diag(conf)';
+%         end
+%         
+%         function TN = getNumTrueNegatives(RE)
+%             numInstances = RE.resultSet.getNumInstances;
+%             FN = RE.getNumFalseNegatives;
+%             TP = RE.getNumTruePositives;
+%             FP = RE.getNumFalsePositives;
+%             TN = numInstances - FN - TP - FP;
+%         end
+%         
+%         function FP = getNumFalsePositives(RE)
+%             conf = RE.resultSet.confusionMatrix;
+%             FP = sum(conf') - diag(conf)';
+%         end
+%         
+%         function FN = getNumFalseNegatives(RE)
+%             conf = RE.resultSet.confusionMatrix;
+%             FN = sum(conf) - diag(conf)';
+%         end
+        
+    end
+end
+
diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.dot b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.dot
new file mode 100644
index 0000000..9eaf551
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ResultEvaluator -> ResultEvaluator;
+
+  ResultEvaluator [URL="ResultEvaluator.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.html b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.html
new file mode 100644
index 0000000..551dd9b
--- /dev/null
+++ b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+experiment/@ResultEvaluator</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+experiment/@ResultEvaluator">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+experiment/@ResultEvaluator">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@ResultEvaluator&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+experiment/@ResultEvaluator</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+experiment/@ResultEvaluator" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ResultEvaluator.html" title="ResultEvaluator" alt="" coords="185,29,180,22,168,15,148,10,123,7,95,5,67,7,42,10,22,15,9,22,5,29,9,37,22,43,42,49,67,52,95,53,123,52,148,49,168,43,180,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.map b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/index.html b/doc/+eegtoolkit/+experiment/@ResultEvaluator/index.html
new file mode 100644
index 0000000..20c55e3
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@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+experiment/@ResultEvaluator</title>
+  <meta name="keywords" content="./+eegtoolkit/+experiment/@ResultEvaluator">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+experiment/@ResultEvaluator">
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+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@ResultEvaluator&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+experiment/@ResultEvaluator</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ResultEvaluator.html">ResultEvaluator</a></td><td>RESULTEVALUATOR class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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+</html>
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diff --git a/doc/+eegtoolkit/+featextraction/@CCA/CCA.html b/doc/+eegtoolkit/+featextraction/@CCA/CCA.html
new file mode 100644
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--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/CCA.html
@@ -0,0 +1,195 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of CCA</title>
+  <meta name="keywords" content="CCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
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+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@CCA</a> &gt; CCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@CCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>CCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CCA.html" class="code" title="">CCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CCA.html" class="code" title="">CCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CCA = CCA(sti_f,chans,fs,numH)</a></li><li><a href="#_sub2" class="code">function extract(CCA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CCA)</a></li><li><a href="#_sub4" class="code">function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)</a></li><li><a href="#_sub5" class="code">function time = getTime(CCA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="CCA.m">CCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="CCA.html" class="code" title="">CCA</a> &lt; eegtoolkit.featextraction.PSDExtractionBase<span class="comment">%FeatureExtractionBase</span>
+0002     <span class="comment">%</span>
+0003     <span class="comment">% works only on our datasets, for other datasets needs modifications</span>
+0004     <span class="comment">%</span>
+0005     properties (Access = public)
+0006         channel;
+0007         avgTime;
+0008         stimulus_freqs;
+0009         FreqSamp;
+0010         NumHarm;
+0011         allFeatures;
+0012     <span class="keyword">end</span>
+0013     methods (Access = public)
+0014         <a name="_sub0" href="#_subfunctions" class="code">function CCA = CCA(sti_f,chans,fs,numH)</a>
+0015             <span class="keyword">if</span> ( nargin ~= 4 )
+0016                 error(<span class="string">'It is needed to define the simulus freqs, the channels, frequency sampling and number of harmonics'</span>);
+0017             <span class="keyword">else</span>
+0018                 CCA.stimulus_freqs = sti_f;
+0019                 CCA.channel = chans;
+0020                 CCA.FreqSamp = fs;
+0021                 CCA.NumHarm = numH;
+0022                 CCA.allFeatures = 0;
+0023             <span class="keyword">end</span>
+0024         <span class="keyword">end</span>
+0025         
+0026         <a name="_sub1" href="#_subfunctions" class="code">function extract(CCA)</a>
+0027             sti_f = CCA.stimulus_freqs;
+0028             mLen=size(CCA.trials{1}.signal,2);
+0029             refSignals=CCA.ck_signalTrans(sti_f,mLen,CCA.FreqSamp,CCA.NumHarm);
+0030             NumStim = size(refSignals,3);
+0031             numTrials = length(CCA.trials);
+0032             <span class="keyword">for</span> i=1:numTrials
+0033                 data = CCA.trials{i}.signal(CCA.channel,:);
+0034                 <span class="keyword">if</span>(CCA.allFeatures == 1)
+0035                     features=NaN*ones(NumStim,min(rank(data),CCA.NumHarm*2));
+0036                     <span class="keyword">for</span> j=1:NumStim
+0037                         [wx1,wy1,r1] = canoncorr(data',refSignals(:,:,j)');
+0038                         features(j,:) = r1;
+0039                     <span class="keyword">end</span>
+0040                     tempfeatures = features(1,:);
+0041                     <span class="keyword">for</span> j=2:NumStim
+0042                         tempfeatures = horzcat(tempfeatures,features(j,:));
+0043                     <span class="keyword">end</span>
+0044                     instances(i,:) = tempfeatures(:);
+0045                     labels(i,1) = floor(CCA.trials{i}.label);
+0046                 <span class="keyword">else</span>
+0047                     features=NaN*ones(NumStim,1);
+0048                     <span class="keyword">for</span> j=1:NumStim
+0049                         <span class="comment">%                     [wx1,wy1,r1] = CCA.cca(data,refSignals(:,:,j));</span>
+0050                         [wx1,wy1,r1] = canoncorr(data',refSignals(:,:,j)');
+0051                         features(j) = max(r1);
+0052                     <span class="keyword">end</span>
+0053                     instances(i,:) = features(:);
+0054                     labels(i,1) = floor(CCA.trials{i}.label);
+0055                 <span class="keyword">end</span>
+0056             <span class="keyword">end</span>
+0057 <span class="comment">%             unique(labels)</span>
+0058             <span class="keyword">if</span> (sum(unique(labels)) == 41)
+0059                 labels(labels==6)=1;
+0060                 labels(labels==7)=2;
+0061                 labels(labels==8)=3;
+0062                 labels(labels==9)=4;
+0063                 labels(labels==11)=5;
+0064             <span class="keyword">end</span>
+0065 <span class="comment">%             unique(labels)</span>
+0066             CCA.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+0067         <span class="keyword">end</span>
+0068         
+0069         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CCA)</a>
+0070             configInfo = sprintf(<span class="string">'CCA'</span>);
+0071         <span class="keyword">end</span>
+0072         
+0073 <span class="comment">%         function [Wx, Wy, r] = cca(CCA,X,Y)</span>
+0074 <span class="comment">%</span>
+0075 <span class="comment">%             % CCA calculate canonical correlations</span>
+0076 <span class="comment">%             %</span>
+0077 <span class="comment">%             % [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation</span>
+0078 <span class="comment">%</span>
+0079 <span class="comment">%             % vectors as columns and r is a vector with corresponding canonical</span>
+0080 <span class="comment">%             % correlations. The correlations are sorted in descending order. X and Y</span>
+0081 <span class="comment">%             % are matrices where each column is a sample. Hence, X and Y must have</span>
+0082 <span class="comment">%             % the same number of columns.</span>
+0083 <span class="comment">%             %</span>
+0084 <span class="comment">%             % Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is</span>
+0085 <span class="comment">%             % then M*L, Wy is N*L and r is L*1.</span>
+0086 <span class="comment">%             %</span>
+0087 <span class="comment">%             %</span>
+0088 <span class="comment">%             % ?? 2000 Magnus Borga, Link?pings universitet</span>
+0089 <span class="comment">%</span>
+0090 <span class="comment">%             % --- Calculate covariance matrices ---??????????????</span>
+0091 <span class="comment">%</span>
+0092 <span class="comment">%             z = [X;Y];</span>
+0093 <span class="comment">%             C = cov(z.');</span>
+0094 <span class="comment">%             sx = size(X,1);   %X??????(??),</span>
+0095 <span class="comment">%             sy = size(Y,1);</span>
+0096 <span class="comment">%             Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);</span>
+0097 <span class="comment">%             Cxy = C(1:sx, sx+1:sx+sy);</span>
+0098 <span class="comment">%             Cyx = Cxy';</span>
+0099 <span class="comment">%             Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);%eye()????????</span>
+0100 <span class="comment">%             invCyy = inv(Cyy);</span>
+0101 <span class="comment">%</span>
+0102 <span class="comment">%             % --- Calcualte Wx and r ---</span>
+0103 <span class="comment">%</span>
+0104 <span class="comment">%             [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); % Basis in X eig????????????</span>
+0105 <span class="comment">%             r = sqrt(real(r));      % Canonical correlations</span>
+0106 <span class="comment">%</span>
+0107 <span class="comment">%             % --- Sort correlations ---</span>
+0108 <span class="comment">%</span>
+0109 <span class="comment">%             V = fliplr(Wx);        % reverse order of eigenvectors??????????????????????i??????????i??????</span>
+0110 <span class="comment">%             r = flipud(diag(r));    % extract eigenvalues and reverse their order</span>
+0111 <span class="comment">%             [r,I]= sort((real(r)));    % sort reversed eigenvalues in ascending order</span>
+0112 <span class="comment">%             r = flipud(r);        % restore sorted eigenvalues into descending order??????????????</span>
+0113 <span class="comment">%             for j = 1:length(I)</span>
+0114 <span class="comment">%                 Wx(:,j) = V(:,I(j));  % sort reversed eigenvectors in ascending order</span>
+0115 <span class="comment">%             end</span>
+0116 <span class="comment">%             Wx = fliplr(Wx);    % restore sorted eigenvectors into descending order</span>
+0117 <span class="comment">%</span>
+0118 <span class="comment">%             % --- Calcualte Wy  ---</span>
+0119 <span class="comment">%</span>
+0120 <span class="comment">%             Wy = invCyy*Cyx*Wx;     % Basis in Y</span>
+0121 <span class="comment">%             % Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy</span>
+0122 <span class="comment">%</span>
+0123 <span class="comment">%         end</span>
+0124         
+0125         <a name="_sub3" href="#_subfunctions" class="code">function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)</a>
+0126             
+0127             p=mLen;<span class="comment">%1250;</span>
+0128             fs=FreqSamp;<span class="comment">%250;</span>
+0129             TP=1/fs:1/fs:p/fs;
+0130             <span class="keyword">for</span> j=1:length(f)
+0131                 tempComp=[];
+0132                 <span class="keyword">for</span> k=1:NumHarm
+0133                     Sinh1=sin(2*pi*k*f(j)*TP);
+0134                     Cosh1=cos(2*pi*k*f(j)*TP);
+0135                     tempComp = [tempComp; Sinh1;Cosh1;];
+0136                 <span class="keyword">end</span>
+0137                 refSignal(:,:,j)=tempComp;
+0138             <span class="keyword">end</span>
+0139         <span class="keyword">end</span>
+0140         <a name="_sub4" href="#_subfunctions" class="code">function time = getTime(CCA)</a>
+0141             time = CCA.avgTime;
+0142         <span class="keyword">end</span>
+0143     <span class="keyword">end</span>
+0144     
+0145 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@CCA/CCA.m b/doc/+eegtoolkit/+featextraction/@CCA/CCA.m
new file mode 100644
index 0000000..fae91b4
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/CCA.m
@@ -0,0 +1,145 @@
+classdef CCA < eegtoolkit.featextraction.PSDExtractionBase%FeatureExtractionBase
+    %
+    % works only on our datasets, for other datasets needs modifications
+    %
+    properties (Access = public)
+        channel;
+        avgTime;
+        stimulus_freqs;
+        FreqSamp;
+        NumHarm;
+        allFeatures;
+    end
+    methods (Access = public)
+        function CCA = CCA(sti_f,chans,fs,numH)
+            if ( nargin ~= 4 )
+                error('It is needed to define the simulus freqs, the channels, frequency sampling and number of harmonics');
+            else
+                CCA.stimulus_freqs = sti_f;
+                CCA.channel = chans;
+                CCA.FreqSamp = fs;
+                CCA.NumHarm = numH;
+                CCA.allFeatures = 0;
+            end
+        end
+        
+        function extract(CCA)
+            sti_f = CCA.stimulus_freqs;
+            mLen=size(CCA.trials{1}.signal,2);
+            refSignals=CCA.ck_signalTrans(sti_f,mLen,CCA.FreqSamp,CCA.NumHarm);
+            NumStim = size(refSignals,3);
+            numTrials = length(CCA.trials);
+            for i=1:numTrials
+                data = CCA.trials{i}.signal(CCA.channel,:);
+                if(CCA.allFeatures == 1)
+                    features=NaN*ones(NumStim,min(rank(data),CCA.NumHarm*2));
+                    for j=1:NumStim
+                        [wx1,wy1,r1] = canoncorr(data',refSignals(:,:,j)');
+                        features(j,:) = r1;
+                    end
+                    tempfeatures = features(1,:);
+                    for j=2:NumStim
+                        tempfeatures = horzcat(tempfeatures,features(j,:));
+                    end
+                    instances(i,:) = tempfeatures(:);
+                    labels(i,1) = floor(CCA.trials{i}.label);
+                else
+                    features=NaN*ones(NumStim,1);
+                    for j=1:NumStim
+                        %                     [wx1,wy1,r1] = CCA.cca(data,refSignals(:,:,j));
+                        [wx1,wy1,r1] = canoncorr(data',refSignals(:,:,j)');
+                        features(j) = max(r1);
+                    end
+                    instances(i,:) = features(:);
+                    labels(i,1) = floor(CCA.trials{i}.label);
+                end
+            end
+%             unique(labels)
+            if (sum(unique(labels)) == 41)
+                labels(labels==6)=1;
+                labels(labels==7)=2;
+                labels(labels==8)=3;
+                labels(labels==9)=4;
+                labels(labels==11)=5;
+            end
+%             unique(labels)
+            CCA.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+        end
+        
+        function configInfo = getConfigInfo(CCA)
+            configInfo = sprintf('CCA');
+        end
+        
+%         function [Wx, Wy, r] = cca(CCA,X,Y)
+%             
+%             % CCA calculate canonical correlations
+%             %
+%             % [Wx Wy r] = cca(X,Y) where Wx and Wy contains the canonical correlation
+%             
+%             % vectors as columns and r is a vector with corresponding canonical
+%             % correlations. The correlations are sorted in descending order. X and Y
+%             % are matrices where each column is a sample. Hence, X and Y must have
+%             % the same number of columns.
+%             %
+%             % Example: If X is M*K and Y is N*K there are L=MIN(M,N) solutions. Wx is
+%             % then M*L, Wy is N*L and r is L*1.
+%             %
+%             %
+%             % ?? 2000 Magnus Borga, Link?pings universitet
+%             
+%             % --- Calculate covariance matrices ---??????????????
+%             
+%             z = [X;Y];
+%             C = cov(z.');
+%             sx = size(X,1);   %X??????(??),
+%             sy = size(Y,1);
+%             Cxx = C(1:sx, 1:sx) + 10^(-8)*eye(sx);
+%             Cxy = C(1:sx, sx+1:sx+sy);
+%             Cyx = Cxy';
+%             Cyy = C(sx+1:sx+sy, sx+1:sx+sy) + 10^(-8)*eye(sy);%eye()????????
+%             invCyy = inv(Cyy);
+%             
+%             % --- Calcualte Wx and r ---
+%             
+%             [Wx,r] = eig(inv(Cxx)*Cxy*invCyy*Cyx); % Basis in X eig????????????
+%             r = sqrt(real(r));      % Canonical correlations
+%             
+%             % --- Sort correlations ---
+%             
+%             V = fliplr(Wx);		% reverse order of eigenvectors??????????????????????i??????????i??????
+%             r = flipud(diag(r));	% extract eigenvalues and reverse their order
+%             [r,I]= sort((real(r)));	% sort reversed eigenvalues in ascending order
+%             r = flipud(r);		% restore sorted eigenvalues into descending order??????????????
+%             for j = 1:length(I)
+%                 Wx(:,j) = V(:,I(j));  % sort reversed eigenvectors in ascending order
+%             end
+%             Wx = fliplr(Wx);	% restore sorted eigenvectors into descending order
+%             
+%             % --- Calcualte Wy  ---
+%             
+%             Wy = invCyy*Cyx*Wx;     % Basis in Y
+%             % Wy = Wy./repmat(sqrt(sum(abs(Wy).^2)),sy,1); % Normalize Wy
+%             
+%         end
+        
+        function refSignal=ck_signalTrans(CCA,f,mLen,FreqSamp,NumHarm)
+            
+            p=mLen;%1250;
+            fs=FreqSamp;%250;
+            TP=1/fs:1/fs:p/fs;
+            for j=1:length(f)
+                tempComp=[];
+                for k=1:NumHarm
+                    Sinh1=sin(2*pi*k*f(j)*TP);
+                    Cosh1=cos(2*pi*k*f(j)*TP);
+                    tempComp = [tempComp; Sinh1;Cosh1;];
+                end
+                refSignal(:,:,j)=tempComp;
+            end
+        end
+        function time = getTime(CCA)
+            time = CCA.avgTime;
+        end
+    end
+    
+end
diff --git a/doc/+eegtoolkit/+featextraction/@CCA/graph.dot b/doc/+eegtoolkit/+featextraction/@CCA/graph.dot
new file mode 100644
index 0000000..d44325c
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  CCA -> CCA;
+
+  CCA [URL="CCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@CCA/graph.html b/doc/+eegtoolkit/+featextraction/@CCA/graph.html
new file mode 100644
index 0000000..ec6c2f3
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@CCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@CCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@CCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@CCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@CCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@CCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="CCA.html" title="CCA" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@CCA/graph.map b/doc/+eegtoolkit/+featextraction/@CCA/graph.map
new file mode 100644
index 0000000..e39843d
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="CCA.html" title="CCA" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
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diff --git a/doc/+eegtoolkit/+featextraction/@CCA/index.html b/doc/+eegtoolkit/+featextraction/@CCA/index.html
new file mode 100644
index 0000000..d997e1b
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@CCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@CCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@CCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@CCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@CCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@CCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="CCA.html">CCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@DWT/DWT.html b/doc/+eegtoolkit/+featextraction/@DWT/DWT.html
new file mode 100644
index 0000000..5e1cd17
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@DWT/DWT.html
@@ -0,0 +1,171 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of DWT</title>
+  <meta name="keywords" content="DWT">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@DWT</a> &gt; DWT.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>DWT
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="DWT.html" class="code" title="">DWT</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="DWT.html" class="code" title="">DWT</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function mDWT = DWT(trials, seconds, channel,levWT,WavFam)</a></li><li><a href="#_sub2" class="code">function extract(mDWT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(mDWT)</a></li><li><a href="#_sub4" class="code">function time = getTime(mDWT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="DWT.m">DWT.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="DWT.html" class="code" title="">DWT</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     
+0003     properties (Access = public)
+0004         channel;
+0005         seconds;
+0006         levelWT;
+0007         WavFamily;
+0008         avgTime;
+0009     <span class="keyword">end</span>
+0010     
+0011     methods (Access = public)
+0012         <a name="_sub0" href="#_subfunctions" class="code">function mDWT = DWT(trials, seconds, channel,levWT,WavFam)</a>
+0013             <span class="keyword">if</span> nargin == 0
+0014                 mDWT.seconds = 0;
+0015                 mDWT.channel = 1;
+0016                 mDWT.levelWT = 5;
+0017                 mDWT.WavFamily = <span class="string">'db1'</span>;
+0018             <span class="keyword">elseif</span> nargin == 1
+0019                 mDWT.trials = trials;
+0020                 mDWT.seconds = 0;
+0021                 mDWT.channel = 1;
+0022                 mDWT.levelWT = 5;
+0023                 mDWT.WavFamily = <span class="string">'db1'</span>;
+0024             <span class="keyword">elseif</span> nargin == 2
+0025                 mDWT.trials = trials;
+0026                 mDWT.channel = 1;
+0027                 mDWT.seconds = seconds;
+0028                 mDWT.levelWT = 5;
+0029                 mDWT.WavFamily = <span class="string">'db1'</span>;
+0030             <span class="keyword">elseif</span> nargin == 3
+0031                 mDWT.trials = trials;
+0032                 mDWT.channel = channel;
+0033                 mDWT.seconds = seconds;
+0034                 mDWT.levelWT = 5;
+0035                 mDWT.WavFamily = <span class="string">'db1'</span>;
+0036             <span class="keyword">elseif</span> nargin == 4
+0037                 mDWT.trials = trials;
+0038                 mDWT.channel = channel;
+0039                 mDWT.seconds = seconds;
+0040                 mDWT.levelWT = levWT;
+0041                 mDWT.WavFamily = <span class="string">'db1'</span>;
+0042             <span class="keyword">elseif</span> nargin ==5
+0043                 mDWT.trials = trials;
+0044                 mDWT.channel = channel;
+0045                 mDWT.seconds = seconds;
+0046                 mDWT.levelWT = levWT;
+0047                 mDWT.WavFamily = WavFam;
+0048             <span class="keyword">else</span>
+0049                 error(<span class="string">'invalid number of arguments'</span>);
+0050             <span class="keyword">end</span>
+0051             mDWT.avgTime = 0;
+0052         <span class="keyword">end</span>
+0053         
+0054         <a name="_sub1" href="#_subfunctions" class="code">function extract(mDWT)</a>
+0055             <span class="keyword">if</span> length(mDWT.seconds)==1
+0056                 numsamples = mDWT.trials{1}.samplingRate * mDWT.seconds;
+0057                 <span class="keyword">if</span> (numsamples == 0)
+0058                     numsamples = size(mDWT.trials{1}.signal(mDWT.channel,:),2);
+0059                 <span class="keyword">end</span>
+0060                 numTrials = length(mDWT.trials);
+0061                 
+0062                 [C L] = wavedec(mDWT.trials{1}.signal(mDWT.channel, 1:numsamples),mDWT.levelWT,mDWT.WavFamily);
+0063                 instances = zeros(numTrials, length(C));
+0064                 labels = zeros(numTrials,1);
+0065             <span class="keyword">elseif</span> length(mDWT.seconds) == 2
+0066                 sampleA = mDWT.trials{1}.samplingRate * mDWT.seconds(1) + 1;
+0067                 sampleB = mDWT.trials{1}.samplingRate * mDWT.seconds(2);
+0068                 numTrials = length(mDWT.trials);
+0069                 [C L] = wavedec(mDWT.trials{1}.signal(mDWT.channel, sampleA:sampleB),mDWT.levelWT,mDWT.WavFamily);
+0070                 instances = zeros(numTrials, length(C));
+0071                 labels = zeros(numTrials,1);
+0072             <span class="keyword">else</span>
+0073                 error(<span class="string">'invalid seconds parameter'</span>);
+0074             <span class="keyword">end</span>
+0075             tic
+0076             <span class="keyword">for</span> i=1:numTrials
+0077                 <span class="keyword">if</span> length(mDWT.seconds) == 1
+0078                     numsamples = mDWT.trials{i}.samplingRate * mDWT.seconds;
+0079                     <span class="keyword">if</span>(numsamples == 0)
+0080                         y = mDWT.trials{i}.signal(mDWT.channel,:);
+0081                     <span class="keyword">else</span>
+0082                         y = mDWT.trials{i}.signal(mDWT.channel, 1:numsamples);
+0083                     <span class="keyword">end</span>
+0084                     <span class="comment">% zero padding to nearest power of 2</span>
+0085                     <span class="keyword">if</span> isa(mDWT.filter,<span class="string">'dfilt.df2sos'</span>)
+0086                         y = filter(mDWT.filter,y);
+0087                     <span class="keyword">elseif</span> isa(mDWT.filter,<span class="string">'dfilt.dffir'</span>)
+0088                         y = filtfilt(mDWT.filter.Numerator,1,y);
+0089                     <span class="keyword">end</span>
+0090                     [C L] = wavedec(y,mDWT.levelWT,mDWT.WavFamily);<span class="comment">%pwelch(y,[],[],512,mDWT.trials{i}.samplingRate,'onesided');</span>
+0091                 <span class="keyword">elseif</span> length(mDWT.seconds) == 2
+0092                     sampleA = mDWT.trials{i}.samplingRate * mDWT.seconds(1) + 1;
+0093                     sampleB = mDWT.trials{i}.samplingRate * mDWT.seconds(2);
+0094                     y = mDWT.trials{i}.signal(mDWT.channel,sampleA:sampleB);
+0095                     <span class="keyword">if</span> isa(mDWT.filter,<span class="string">'dfilt.df2sos'</span>) || isa(mDWT.filter,<span class="string">'dfilt.df2'</span>)
+0096                         y = filter(mDWT.filter,y);
+0097                     <span class="keyword">elseif</span> isa(mDWT.filter,<span class="string">'dfilt.dffir'</span>)
+0098                         y = filtfilt(mDWT.filter.Numerator,1,y);
+0099                     <span class="keyword">end</span>
+0100                     [C L] = wavedec(y,mDWT.levelWT,mDWT.WavFamily);<span class="comment">%pwelch(y,[],[],512,mDWT.trials{i}.samplingRate,'onesided');</span>
+0101                 <span class="keyword">else</span>
+0102                     error(<span class="string">'invalid seconds parameter'</span>);
+0103                 <span class="keyword">end</span>
+0104                 instances(i,:) = C;
+0105                 labels(i,1) = floor(mDWT.trials{i}.label);
+0106             <span class="keyword">end</span>
+0107             mDWT.avgTime = toc/numTrials;
+0108             mDWT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+0109         <span class="keyword">end</span>
+0110         
+0111         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(mDWT)</a>
+0112             configInfo = sprintf(<span class="string">'DWT\tchannel:%d\tseconds:%d\tlevelWT:%d\tWavFamily:%s'</span>,mDWT.channel,mDWT.seconds,mDWT.levelWT,mDWT.WavFamily);
+0113         <span class="keyword">end</span>
+0114         
+0115                         
+0116         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(mDWT)</a>
+0117             time = mDWT.avgTime;
+0118         <span class="keyword">end</span>
+0119     <span class="keyword">end</span>
+0120     
+0121 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@DWT/DWT.m b/doc/+eegtoolkit/+featextraction/@DWT/DWT.m
new file mode 100644
index 0000000..6918d53
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@DWT/DWT.m
@@ -0,0 +1,121 @@
+classdef DWT < eegtoolkit.featextraction.FeatureExtractionBase
+    
+    properties (Access = public)
+        channel;
+        seconds;
+        levelWT;
+        WavFamily;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function mDWT = DWT(trials, seconds, channel,levWT,WavFam)
+            if nargin == 0
+                mDWT.seconds = 0;
+                mDWT.channel = 1;
+                mDWT.levelWT = 5;
+                mDWT.WavFamily = 'db1';
+            elseif nargin == 1
+                mDWT.trials = trials;
+                mDWT.seconds = 0;
+                mDWT.channel = 1;
+                mDWT.levelWT = 5;
+                mDWT.WavFamily = 'db1';
+            elseif nargin == 2
+                mDWT.trials = trials;
+                mDWT.channel = 1;
+                mDWT.seconds = seconds;
+                mDWT.levelWT = 5;
+                mDWT.WavFamily = 'db1';
+            elseif nargin == 3
+                mDWT.trials = trials;
+                mDWT.channel = channel;
+                mDWT.seconds = seconds;
+                mDWT.levelWT = 5;
+                mDWT.WavFamily = 'db1';
+            elseif nargin == 4
+                mDWT.trials = trials;
+                mDWT.channel = channel;
+                mDWT.seconds = seconds;
+                mDWT.levelWT = levWT;
+                mDWT.WavFamily = 'db1';
+            elseif nargin ==5
+                mDWT.trials = trials;
+                mDWT.channel = channel;
+                mDWT.seconds = seconds;
+                mDWT.levelWT = levWT;
+                mDWT.WavFamily = WavFam;
+            else
+                error('invalid number of arguments');
+            end
+            mDWT.avgTime = 0;
+        end
+        
+        function extract(mDWT)
+            if length(mDWT.seconds)==1
+                numsamples = mDWT.trials{1}.samplingRate * mDWT.seconds;
+                if (numsamples == 0)
+                    numsamples = size(mDWT.trials{1}.signal(mDWT.channel,:),2);
+                end
+                numTrials = length(mDWT.trials);
+                
+                [C L] = wavedec(mDWT.trials{1}.signal(mDWT.channel, 1:numsamples),mDWT.levelWT,mDWT.WavFamily);
+                instances = zeros(numTrials, length(C));
+                labels = zeros(numTrials,1);
+            elseif length(mDWT.seconds) == 2
+                sampleA = mDWT.trials{1}.samplingRate * mDWT.seconds(1) + 1;
+                sampleB = mDWT.trials{1}.samplingRate * mDWT.seconds(2);
+                numTrials = length(mDWT.trials);
+                [C L] = wavedec(mDWT.trials{1}.signal(mDWT.channel, sampleA:sampleB),mDWT.levelWT,mDWT.WavFamily);
+                instances = zeros(numTrials, length(C));
+                labels = zeros(numTrials,1);
+            else
+                error('invalid seconds parameter');
+            end
+            tic
+            for i=1:numTrials
+                if length(mDWT.seconds) == 1
+                    numsamples = mDWT.trials{i}.samplingRate * mDWT.seconds;
+                    if(numsamples == 0)
+                        y = mDWT.trials{i}.signal(mDWT.channel,:);
+                    else
+                        y = mDWT.trials{i}.signal(mDWT.channel, 1:numsamples);
+                    end
+                    % zero padding to nearest power of 2
+                    if isa(mDWT.filter,'dfilt.df2sos')
+                        y = filter(mDWT.filter,y);
+                    elseif isa(mDWT.filter,'dfilt.dffir')
+                        y = filtfilt(mDWT.filter.Numerator,1,y);
+                    end
+                    [C L] = wavedec(y,mDWT.levelWT,mDWT.WavFamily);%pwelch(y,[],[],512,mDWT.trials{i}.samplingRate,'onesided');
+                elseif length(mDWT.seconds) == 2
+                    sampleA = mDWT.trials{i}.samplingRate * mDWT.seconds(1) + 1;
+                    sampleB = mDWT.trials{i}.samplingRate * mDWT.seconds(2);
+                    y = mDWT.trials{i}.signal(mDWT.channel,sampleA:sampleB);
+                    if isa(mDWT.filter,'dfilt.df2sos') || isa(mDWT.filter,'dfilt.df2')
+                        y = filter(mDWT.filter,y);
+                    elseif isa(mDWT.filter,'dfilt.dffir')
+                        y = filtfilt(mDWT.filter.Numerator,1,y);
+                    end
+                    [C L] = wavedec(y,mDWT.levelWT,mDWT.WavFamily);%pwelch(y,[],[],512,mDWT.trials{i}.samplingRate,'onesided');
+                else
+                    error('invalid seconds parameter');
+                end
+                instances(i,:) = C;
+                labels(i,1) = floor(mDWT.trials{i}.label);
+            end
+            mDWT.avgTime = toc/numTrials;
+            mDWT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+        
+        function configInfo = getConfigInfo(mDWT)
+            configInfo = sprintf('DWT\tchannel:%d\tseconds:%d\tlevelWT:%d\tWavFamily:%s',mDWT.channel,mDWT.seconds,mDWT.levelWT,mDWT.WavFamily);
+        end
+        
+                        
+        function time = getTime(mDWT)
+            time = mDWT.avgTime;
+        end
+    end
+    
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@DWT/graph.dot b/doc/+eegtoolkit/+featextraction/@DWT/graph.dot
new file mode 100644
index 0000000..f950fda
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@DWT/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  DWT -> DWT;
+
+  DWT [URL="DWT.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@DWT/graph.html b/doc/+eegtoolkit/+featextraction/@DWT/graph.html
new file mode 100644
index 0000000..3982477
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@DWT/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@DWT</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@DWT">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@DWT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@DWT</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@DWT" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="DWT.html" title="DWT" alt="" coords="88,29,86,22,80,15,71,10,60,7,47,5,34,7,22,10,13,15,7,22,5,29,7,37,13,43,22,49,34,52,47,53,60,52,71,49,80,43,86,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@DWT/graph.map b/doc/+eegtoolkit/+featextraction/@DWT/graph.map
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diff --git a/doc/+eegtoolkit/+featextraction/@DWT/index.html b/doc/+eegtoolkit/+featextraction/@DWT/index.html
new file mode 100644
index 0000000..b9380d7
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@DWT/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@DWT</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@DWT">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@DWT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@DWT</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="DWT.html">DWT</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html
new file mode 100644
index 0000000..8c3656b
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html
@@ -0,0 +1,86 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ERRPFeatures</title>
+  <meta name="keywords" content="ERRPFeatures">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@ERRPFeatures</a> &gt; ERRPFeatures.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ERRPFeatures
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ERRPFeatures.html" class="code" title="">ERRPFeatures</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ERRPFeatures.html" class="code" title="">ERRPFeatures</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function ERRP = ERRPFeatures()</a></li><li><a href="#_sub2" class="code">function extract(ERRP)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(ERRP)</a></li><li><a href="#_sub4" class="code">function time = getTime(ERRP)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ERRPFeatures.m">ERRPFeatures.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="ERRPFeatures.html" class="code" title="">ERRPFeatures</a> &lt; eegtoolkit.featextraction.PSDExtractionBase<span class="comment">%FeatureExtractionBase</span>
+0002     properties (Access = public)
+0003         channel;
+0004         avgTime;
+0005 <span class="comment">%         downSampleFactor;</span>
+0006     <span class="keyword">end</span>
+0007     methods (Access = public)
+0008         <a name="_sub0" href="#_subfunctions" class="code">function ERRP = ERRPFeatures()</a>
+0009 <span class="comment">%             ERRP.downSampleFactor = 8;</span>
+0010             ERRP.channel = 1;
+0011         <span class="keyword">end</span>
+0012         
+0013         <a name="_sub1" href="#_subfunctions" class="code">function extract(ERRP)</a>
+0014             
+0015             numTrials = length(ERRP.trials);
+0016             [~,numSamples]  =  size(ERRP.trials{1}.signal(ERRP.channel,:));
+0017 <span class="comment">%             numFeatures = floor(numSamples/ERRP.downSampleFactor);</span>
+0018             instances = zeros(numTrials,numSamples);
+0019             labels = zeros(numTrials,1);
+0020             <span class="keyword">for</span> i=1:numTrials
+0021                 instances(i,:) = ERRP.trials{i}.signal(ERRP.channel,:);
+0022                 labels(i) = ERRP.trials{i}.label;
+0023             <span class="keyword">end</span>
+0024             ERRP.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+0025         <span class="keyword">end</span>
+0026         
+0027         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(ERRP)</a>
+0028             configInfo = sprintf(<span class="string">'ERRP features'</span>);
+0029         <span class="keyword">end</span>
+0030         
+0031         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(ERRP)</a>
+0032             time = ERRP.avgTime;
+0033         <span class="keyword">end</span>
+0034     <span class="keyword">end</span>
+0035     
+0036 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.m b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.m
new file mode 100644
index 0000000..11474dc
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.m
@@ -0,0 +1,36 @@
+classdef ERRPFeatures < eegtoolkit.featextraction.PSDExtractionBase%FeatureExtractionBase
+    properties (Access = public)
+        channel;
+        avgTime;
+%         downSampleFactor;
+    end
+    methods (Access = public)
+        function ERRP = ERRPFeatures()
+%             ERRP.downSampleFactor = 8;
+            ERRP.channel = 1;
+        end
+        
+        function extract(ERRP)
+            
+            numTrials = length(ERRP.trials);
+            [~,numSamples]  =  size(ERRP.trials{1}.signal(ERRP.channel,:));
+%             numFeatures = floor(numSamples/ERRP.downSampleFactor);
+            instances = zeros(numTrials,numSamples);
+            labels = zeros(numTrials,1);
+            for i=1:numTrials
+                instances(i,:) = ERRP.trials{i}.signal(ERRP.channel,:);
+                labels(i) = ERRP.trials{i}.label;
+            end
+            ERRP.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+        end
+        
+        function configInfo = getConfigInfo(ERRP)
+            configInfo = sprintf('ERRP features');
+        end
+        
+        function time = getTime(ERRP)
+            time = ERRP.avgTime;
+        end
+    end
+    
+end
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.dot b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.dot
new file mode 100644
index 0000000..1fef1ce
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ERRPFeatures -> ERRPFeatures;
+
+  ERRPFeatures [URL="ERRPFeatures.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html
new file mode 100644
index 0000000..488795b
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures" border="2" style="color:#000;">  
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diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html
new file mode 100644
index 0000000..5803cba
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@ERRPFeatures</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@ERRPFeatures</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ERRPFeatures.html">ERRPFeatures</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/FFT.html b/doc/+eegtoolkit/+featextraction/@FFT/FFT.html
new file mode 100644
index 0000000..e9f760a
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/FFT.html
@@ -0,0 +1,139 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FFT</title>
+  <meta name="keywords" content="FFT">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@FFT</a> &gt; FFT.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FFT
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FFT.html" class="code" title="">FFT</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FFT.html" class="code" title="">FFT</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function mFFT = FFT(trials, seconds, channel,nfft)</a></li><li><a href="#_sub2" class="code">function extract(mFFT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(mFFT)</a></li><li><a href="#_sub4" class="code">function time = getTime(mFFT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FFT.m">FFT.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="FFT.html" class="code" title="">FFT</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     
+0003     properties (Access = public)
+0004         channel;
+0005         seconds;
+0006         nfft;
+0007         avgTime;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods (Access = public)
+0011         <a name="_sub0" href="#_subfunctions" class="code">function mFFT = FFT(trials, seconds, channel,nfft)</a>
+0012             <span class="keyword">if</span> nargin == 0
+0013                 mFFT.seconds = 0;
+0014                 mFFT.channel = 1;
+0015                 mFFT.nfft = 512;
+0016             <span class="keyword">elseif</span> nargin == 1
+0017                 mFFT.trials = trials;
+0018                 mFFT.seconds = 0;
+0019                 mFFT.channel = 1;
+0020                 mFFT.nfft = 512;
+0021             <span class="keyword">elseif</span> nargin == 2
+0022                 mFFT.trials = trials;
+0023                 mFFT.channel = 1;
+0024                 mFFT.seconds = seconds;
+0025                 mFFT.nfft = 512;
+0026             <span class="keyword">elseif</span> nargin == 3
+0027                 mFFT.trials = trials;
+0028                 mFFT.channel = channel;
+0029                 mFFT.seconds = seconds;
+0030                 mFFT.nfft = 512;
+0031             <span class="keyword">elseif</span> nargin == 4
+0032                 mFFT.trials = trials;
+0033                 mFFT.channel = channel;
+0034                 mFFT.seconds = seconds;
+0035                 mFFT.nfft = nfft;
+0036                 error(<span class="string">'invalid number of arguments'</span>);
+0037             <span class="keyword">end</span>
+0038         <span class="keyword">end</span>
+0039         
+0040         <a name="_sub1" href="#_subfunctions" class="code">function extract(mFFT)</a>
+0041             NUM_FEATURES = mFFT.nfft/2+1;
+0042             numTrials = length(mFFT.trials);
+0043             instances = zeros(numTrials, NUM_FEATURES);
+0044             labels = zeros(numTrials,1);
+0045             tic
+0046             <span class="keyword">for</span> i=1:numTrials
+0047                 <span class="keyword">if</span> length(mFFT.seconds) == 1
+0048                 numsamples = mFFT.trials{i}.samplingRate * mFFT.seconds;
+0049                 <span class="keyword">if</span>(numsamples == 0)
+0050                     y = mFFT.trials{i}.signal(mFFT.channel,:);
+0051                 <span class="keyword">else</span>
+0052                     y = mFFT.trials{i}.signal(mFFT.channel, 1:numsamples);
+0053                 <span class="keyword">end</span>
+0054                 <span class="keyword">elseif</span> length(mFFT.seconds) == 2
+0055                     sampleA = mFFT.trials{i}.samplingRate * mFFT.seconds(1) + 1;
+0056                     sampleB = mFFT.trials{i}.samplingRate * mFFT.seconds(2);
+0057                     y = mFFT.trials{i}.signal(mFFT.channel, sampleA:sampleB);
+0058                 <span class="keyword">else</span>
+0059                     
+0060                     error (<span class="string">'invalid seconds parameter'</span>);
+0061                 <span class="keyword">end</span>
+0062                 <span class="keyword">if</span> isa(mFFT.filter,<span class="string">'dfilt.df2sos'</span>) || isa(mFFT.filter,<span class="string">'dfilt.df2'</span>)
+0063                     y = filter(mFFT.filter,y);
+0064                 <span class="keyword">elseif</span> isa(mFFT.filter,<span class="string">'dfilt.dffir'</span>)
+0065                     y = filtfilt(mFFT.filter.Numerator,1,y);
+0066                 <span class="keyword">end</span>
+0067                 <span class="comment">%Y = fft(y,(NUM_FEATURES-1)*2)/((NUM_FEATURES-1)*2);</span>
+0068                 <span class="comment">%f = Fs/2*linspace(0,1,NFFT/2+1);</span>
+0069                 <span class="comment">%pyy = abs(Y(1:(NUM_FEATURES-1)*2/2+1)).^2;</span>
+0070                 [pyy,f] = periodogram(y,[],mFFT.nfft,mFFT.trials{i}.samplingRate);
+0071                 instances(i,:) = pyy;
+0072                 labels(i,1) = floor(mFFT.trials{i}.label);
+0073             <span class="keyword">end</span>
+0074             mFFT.avgTime = toc/numTrials;
+0075             mFFT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+0076         <span class="keyword">end</span>
+0077         
+0078         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(mFFT)</a>
+0079             configInfo = sprintf(<span class="string">'FFT\tchannel:%d\tseconds:%d\tnfft:%d'</span>,mFFT.channel,mFFT.seconds,mFFT.nfft);
+0080         <span class="keyword">end</span>
+0081         
+0082                         
+0083         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(mFFT)</a>
+0084             time = mFFT.avgTime;
+0085         <span class="keyword">end</span>
+0086     <span class="keyword">end</span>
+0087    
+0088 <span class="keyword">end</span>
+0089</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/FFT.m b/doc/+eegtoolkit/+featextraction/@FFT/FFT.m
new file mode 100644
index 0000000..f0f986f
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/FFT.m
@@ -0,0 +1,89 @@
+classdef FFT < eegtoolkit.featextraction.FeatureExtractionBase
+    
+    properties (Access = public)
+        channel;
+        seconds;
+        nfft;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function mFFT = FFT(trials, seconds, channel,nfft)
+            if nargin == 0
+                mFFT.seconds = 0;
+                mFFT.channel = 1;
+                mFFT.nfft = 512;
+            elseif nargin == 1
+                mFFT.trials = trials;
+                mFFT.seconds = 0;
+                mFFT.channel = 1;
+                mFFT.nfft = 512;
+            elseif nargin == 2
+                mFFT.trials = trials;
+                mFFT.channel = 1;
+                mFFT.seconds = seconds;
+                mFFT.nfft = 512;
+            elseif nargin == 3
+                mFFT.trials = trials;
+                mFFT.channel = channel;
+                mFFT.seconds = seconds;
+                mFFT.nfft = 512;
+            elseif nargin == 4
+                mFFT.trials = trials;
+                mFFT.channel = channel;
+                mFFT.seconds = seconds;
+                mFFT.nfft = nfft;
+                error('invalid number of arguments');
+            end
+        end
+        
+        function extract(mFFT)
+            NUM_FEATURES = mFFT.nfft/2+1;
+            numTrials = length(mFFT.trials);
+            instances = zeros(numTrials, NUM_FEATURES);
+            labels = zeros(numTrials,1);
+            tic
+            for i=1:numTrials
+                if length(mFFT.seconds) == 1
+                numsamples = mFFT.trials{i}.samplingRate * mFFT.seconds;
+                if(numsamples == 0)
+                    y = mFFT.trials{i}.signal(mFFT.channel,:);
+                else
+                    y = mFFT.trials{i}.signal(mFFT.channel, 1:numsamples);
+                end
+                elseif length(mFFT.seconds) == 2
+                    sampleA = mFFT.trials{i}.samplingRate * mFFT.seconds(1) + 1;
+                    sampleB = mFFT.trials{i}.samplingRate * mFFT.seconds(2);
+                    y = mFFT.trials{i}.signal(mFFT.channel, sampleA:sampleB);
+                else
+                    
+                    error ('invalid seconds parameter');
+                end
+                if isa(mFFT.filter,'dfilt.df2sos') || isa(mFFT.filter,'dfilt.df2')
+                    y = filter(mFFT.filter,y);
+                elseif isa(mFFT.filter,'dfilt.dffir')
+                    y = filtfilt(mFFT.filter.Numerator,1,y);
+                end
+                %Y = fft(y,(NUM_FEATURES-1)*2)/((NUM_FEATURES-1)*2);
+                %f = Fs/2*linspace(0,1,NFFT/2+1);
+                %pyy = abs(Y(1:(NUM_FEATURES-1)*2/2+1)).^2;
+                [pyy,f] = periodogram(y,[],mFFT.nfft,mFFT.trials{i}.samplingRate);
+                instances(i,:) = pyy;
+                labels(i,1) = floor(mFFT.trials{i}.label);
+            end
+            mFFT.avgTime = toc/numTrials;
+            mFFT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+        
+        function configInfo = getConfigInfo(mFFT)
+            configInfo = sprintf('FFT\tchannel:%d\tseconds:%d\tnfft:%d',mFFT.channel,mFFT.seconds,mFFT.nfft);
+        end
+        
+                        
+        function time = getTime(mFFT)
+            time = mFFT.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/graph.dot b/doc/+eegtoolkit/+featextraction/@FFT/graph.dot
new file mode 100644
index 0000000..8f0dec4
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FFT -> FFT;
+
+  FFT [URL="FFT.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/graph.html b/doc/+eegtoolkit/+featextraction/@FFT/graph.html
new file mode 100644
index 0000000..c0a8cd9
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@FFT</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@FFT">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@FFT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@FFT</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@FFT" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FFT.html" title="FFT" alt="" coords="77,29,76,22,70,15,62,10,52,7,41,5,30,7,20,10,12,15,7,22,5,29,7,37,12,43,20,49,30,52,41,53,52,52,62,49,70,43,76,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/graph.map b/doc/+eegtoolkit/+featextraction/@FFT/graph.map
new file mode 100644
index 0000000..a5a5801
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="FFT.html" title="FFT" alt="" coords="77,29,76,22,70,15,62,10,52,7,41,5,30,7,20,10,12,15,7,22,5,29,7,37,12,43,20,49,30,52,41,53,52,52,62,49,70,43,76,37">
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diff --git a/doc/+eegtoolkit/+featextraction/@FFT/index.html b/doc/+eegtoolkit/+featextraction/@FFT/index.html
new file mode 100644
index 0000000..0e4fd7b
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FFT/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@FFT</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@FFT">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@FFT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@FFT</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FFT.html">FFT</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html
new file mode 100644
index 0000000..1c93476
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html
@@ -0,0 +1,134 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FeatureExtractionBase</title>
+  <meta name="keywords" content="FeatureExtractionBase">
+  <meta name="description" content="Abstract class for feature extraction. Implement the functions for any">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@FeatureExtractionBase</a> &gt; FeatureExtractionBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FeatureExtractionBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>Abstract class for feature extraction. Implement the functions for any</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Abstract class for feature extraction. Implement the functions for any
+ preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+ rereferencing, etc.
+ 
+ Properties:
+ instanceSet: Output - the features in an InstanceSet structure
+ trials: Input - the signals in a cell of Trial structures
+ 
+ Functions:
+Implement this function to extract the features from the input Trials 
+and return the features in an instanceSet
+   out = obj.extract(in);
+Info &amp; run time so that the experiments are easily documented. configInfo
+is a string with the configuration information and time is of type double.
+   configInfo = obj.getConfigInfo();
+   time = obj.getTime();</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FeatureExtractionBase.html" class="code" title="">FeatureExtractionBase</a>	Abstract class for feature extraction. Implement the functions for any</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FeatureExtractionBase.html" class="code" title="">FeatureExtractionBase</a>	Abstract class for feature extraction. Implement the functions for any</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function instances = getInstances(obj)</a></li><li><a href="#_sub2" class="code">function labels = getLabels(obj)</a></li><li><a href="#_sub3" class="code">function dataset = getDataset(obj)</a></li><li><a href="#_sub4" class="code">function instanceSet = getInstanceSet(obj)</a></li><li><a href="#_sub5" class="code">function writeCSV(obj, csvname)</a></li><li><a href="#_sub6" class="code">function writeArff(obj, fname)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FeatureExtractionBase.m">FeatureExtractionBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Abstract class for feature extraction. Implement the functions for any</span>
+0002 <span class="comment">% preprocessing step (e.g. filtering, artifact removal, sub-sampling,</span>
+0003 <span class="comment">% rereferencing, etc.</span>
+0004 <span class="comment">%</span>
+0005 <span class="comment">% Properties:</span>
+0006 <span class="comment">% instanceSet: Output - the features in an InstanceSet structure</span>
+0007 <span class="comment">% trials: Input - the signals in a cell of Trial structures</span>
+0008 <span class="comment">%</span>
+0009 <span class="comment">% Functions:</span>
+0010 <span class="comment">%Implement this function to extract the features from the input Trials</span>
+0011 <span class="comment">%and return the features in an instanceSet</span>
+0012 <span class="comment">%   out = obj.extract(in);</span>
+0013 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0014 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0015 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0016 <span class="comment">%   time = obj.getTime();</span>
+0017 
+0018 
+0019 classdef (Abstract) <a href="FeatureExtractionBase.html" class="code" title="">FeatureExtractionBase</a> &lt; handle
+0020     <span class="comment">%Base class for a feature transformer</span>
+0021     <span class="comment">%For writing your own FeatureTransformer extend this class and</span>
+0022     <span class="comment">%implement the 'transform' function</span>
+0023     properties (Access = public)
+0024         instanceSet; <span class="comment">% Output: The dataset</span>
+0025         trials;<span class="comment">% Input: The trial signals</span>
+0026         filter;
+0027     <span class="keyword">end</span>
+0028     
+0029     methods (Abstract = true)
+0030         obj = extract(obj);
+0031         configInfo = getConfigInfo(obj);
+0032         time = getTime(obj);
+0033     <span class="keyword">end</span>
+0034     
+0035     methods (Access = public)
+0036         <a name="_sub0" href="#_subfunctions" class="code">function instances = getInstances(obj)</a>
+0037             <span class="comment">%Get the instances (no class labels)</span>
+0038             instances = obj.instanceSet.getInstances;
+0039         <span class="keyword">end</span>
+0040         <a name="_sub1" href="#_subfunctions" class="code">function labels = getLabels(obj)</a>
+0041             <span class="comment">%Get the labels</span>
+0042             labels = obj.instanceSet.getLabels;
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub2" href="#_subfunctions" class="code">function dataset = getDataset(obj)</a>
+0046             <span class="comment">% same with getInstances but includes the labels as the last</span>
+0047             <span class="comment">% row</span>
+0048             dataset = obj.instanceSet.getDataset;
+0049         <span class="keyword">end</span>
+0050         
+0051         <a name="_sub3" href="#_subfunctions" class="code">function instanceSet = getInstanceSet(obj)</a>
+0052             <span class="comment">% Get the dataset as an 'InstanceSet' class object</span>
+0053             instanceSet = obj.instanceSet;
+0054         <span class="keyword">end</span>
+0055         <a name="_sub4" href="#_subfunctions" class="code">function writeCSV(obj, csvname)</a>
+0056             <span class="comment">% write the dataset to a csv file</span>
+0057             <span class="comment">% Example:</span>
+0058             <span class="comment">%   obj.writeCSV('data.csv');</span>
+0059             obj.instanceSet.writeCSV(csvname);
+0060         <span class="keyword">end</span>
+0061         <a name="_sub5" href="#_subfunctions" class="code">function writeArff(obj, fname)</a>
+0062             <span class="comment">% write the dataset to a weka-readable file (arff)</span>
+0063             <span class="comment">% Caution: filename without extension</span>
+0064             <span class="comment">% Example:</span>
+0065             <span class="comment">%   obj.writeArff('data')</span>
+0066             obj.instanceSet.writeArff(fname);
+0067         <span class="keyword">end</span>
+0068     <span class="keyword">end</span>
+0069 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
new file mode 100644
index 0000000..29ef454
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
@@ -0,0 +1,69 @@
+% Abstract class for feature extraction. Implement the functions for any
+% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+% rereferencing, etc.
+% 
+% Properties:
+% instanceSet: Output - the features in an InstanceSet structure
+% trials: Input - the signals in a cell of Trial structures
+% 
+% Functions:
+%Implement this function to extract the features from the input Trials 
+%and return the features in an instanceSet
+%   out = obj.extract(in);
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+
+classdef (Abstract) FeatureExtractionBase < handle
+    %Base class for a feature transformer
+    %For writing your own FeatureTransformer extend this class and
+    %implement the 'transform' function
+    properties (Access = public)
+        instanceSet; % Output: The dataset
+        trials;% Input: The trial signals
+        filter;
+    end
+    
+    methods (Abstract = true)
+        obj = extract(obj);
+        configInfo = getConfigInfo(obj);
+        time = getTime(obj);
+    end
+    
+    methods (Access = public)
+        function instances = getInstances(obj)
+            %Get the instances (no class labels)
+            instances = obj.instanceSet.getInstances;
+        end
+        function labels = getLabels(obj)
+            %Get the labels
+            labels = obj.instanceSet.getLabels;
+        end
+        
+        function dataset = getDataset(obj)
+            % same with getInstances but includes the labels as the last
+            % row
+            dataset = obj.instanceSet.getDataset;
+        end
+        
+        function instanceSet = getInstanceSet(obj)
+            % Get the dataset as an 'InstanceSet' class object
+            instanceSet = obj.instanceSet;
+        end
+        function writeCSV(obj, csvname)
+            % write the dataset to a csv file
+            % Example:
+            %   obj.writeCSV('data.csv');
+            obj.instanceSet.writeCSV(csvname);
+        end
+        function writeArff(obj, fname)
+            % write the dataset to a weka-readable file (arff)
+            % Caution: filename without extension
+            % Example:
+            %   obj.writeArff('data')            
+            obj.instanceSet.writeArff(fname);
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.dot b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.dot
new file mode 100644
index 0000000..699ad24
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FeatureExtractionBase -> FeatureExtractionBase;
+
+  FeatureExtractionBase [URL="FeatureExtractionBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html
new file mode 100644
index 0000000..10916ea
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FeatureExtractionBase.html" title="FeatureExtractionBase" alt="" coords="247,29,241,22,223,15,197,10,163,7,125,5,88,7,54,10,27,15,10,22,4,29,10,37,27,43,54,49,88,52,125,53,163,52,197,49,223,43,241,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.map b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html
new file mode 100644
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@FeatureExtractionBase</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
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+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FeatureExtractionBase.html">FeatureExtractionBase</a></td><td>Abstract class for feature extraction. Implement the functions for any </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html b/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html
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@@ -0,0 +1,150 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Goertzel</title>
+  <meta name="keywords" content="Goertzel">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@Goertzel</a> &gt; Goertzel.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Goertzel
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Goertzel.html" class="code" title="">Goertzel</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Goertzel.html" class="code" title="">Goertzel</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function GT = Goertzel(trials, seconds, channel, nfft)</a></li><li><a href="#_sub2" class="code">function extract(GT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(GT)</a></li><li><a href="#_sub4" class="code">function time = getTime(GT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Goertzel.m">Goertzel.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Goertzel.html" class="code" title="">Goertzel</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002 <span class="comment">%Computes the psd using the welch method</span>
+0003 <span class="comment">%Usage:</span>
+0004 <span class="comment">%   session = eegtoolkit.util.Session();</span>
+0005 <span class="comment">%   session.loadSubject(1);</span>
+0006 <span class="comment">%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);</span>
+0007 <span class="comment">%Specify the channel to be used (default = 126)</span>
+0008 <span class="comment">%   pwt.channel = 150;</span>
+0009 <span class="comment">%Specify the number of seconds to be used (default = 0, use all signal)</span>
+0010 <span class="comment">%   pwt.seconds = 3;</span>
+0011 <span class="comment">%Specify the nfft parameter (default = 512, computes 257 features)</span>
+0012 <span class="comment">%   pwt.nfft = 512;</span>
+0013 <span class="comment">%Transform the signal</span>
+0014 <span class="comment">%   pwt.transform();</span>
+0015     properties (Access = public)
+0016         channel;
+0017         seconds;
+0018         nfft;
+0019         pff;
+0020         avgTime;
+0021     <span class="keyword">end</span>
+0022     
+0023     methods (Access = public)
+0024         <a name="_sub0" href="#_subfunctions" class="code">function GT = Goertzel(trials, seconds, channel, nfft)</a>
+0025 <span class="comment">%             if ~iscell(trials)</span>
+0026 <span class="comment">%                 error('trials must be cell array of Trial object');</span>
+0027 <span class="comment">%             end</span>
+0028             <span class="keyword">if</span> nargin == 0
+0029                 GT.trials = {};
+0030                 GT.seconds = 0;
+0031                 GT.channel = 1;
+0032                 GT.nfft = 512;
+0033             <span class="keyword">elseif</span> nargin == 1
+0034                 GT.trials = trials;
+0035                 GT.seconds = 0;
+0036                 GT.channel = 1;
+0037                 GT.nfft = 512;
+0038             <span class="keyword">elseif</span> nargin == 2
+0039                 GT.trials = trials;
+0040                 GT.channel = 1;
+0041                 GT.seconds = seconds;
+0042                 GT.nfft = 512;
+0043             <span class="keyword">elseif</span> nargin == 3
+0044                 GT.trials = trials;
+0045                 GT.channel = channel;
+0046                 GT.seconds = seconds;
+0047                 GT.nfft = 512;
+0048             <span class="keyword">elseif</span> nargin == 4
+0049                 GT.trials = trials;
+0050                 GT.channel = channel;
+0051                 GT.seconds = seconds;
+0052                 GT.nfft = nfft;
+0053             <span class="keyword">else</span>
+0054 <span class="comment">%                 error('invalid number of arguments');</span>
+0055             <span class="keyword">end</span>
+0056         <span class="keyword">end</span>
+0057         
+0058         <a name="_sub1" href="#_subfunctions" class="code">function extract(GT)</a>
+0059            
+0060             numFeatures = length(GT.nfft);
+0061             numTrials = length(GT.trials);
+0062             instances = zeros(numTrials, numFeatures);
+0063             labels = zeros(numTrials,1);
+0064 <span class="comment">%             PWT.instances = zeros(numTrials, numFeatures);</span>
+0065 <span class="comment">%             PWT.labels = zeros(numTrials,1);</span>
+0066             tic;
+0067             <span class="keyword">for</span> i=1:numTrials
+0068                 numsamples = GT.trials{i}.samplingRate * GT.seconds;
+0069                 <span class="keyword">if</span>(numsamples == 0)
+0070                     y = GT.trials{i}.signal(GT.channel,:);
+0071                 <span class="keyword">else</span>
+0072                     y = GT.trials{i}.signal(GT.channel, 1:numsamples);
+0073                 <span class="keyword">end</span>
+0074 <span class="comment">%                 N = (length(y)+1)/2;</span>
+0075 <span class="comment">%                 f = (PWT.trials{i}.samplingRate/2)/N*(0:N-1);</span>
+0076 <span class="comment">%                 indxs = find(f&gt;1.2e3 &amp; f&lt;1.3e3);</span>
+0077 <span class="comment">%                 X = goertzel(x,indxs);</span>
+0078                 freq_indices = round(GT.nfft/GT.trials{i}.samplingRate*length(y)) + 1;
+0079 <span class="comment">%                 ff = [0:1/512:1/2]*250;</span>
+0080 <span class="comment">%                 freq_indices = round(ff/PWT.trials{i}.samplingRate*length(y))+1</span>
+0081                 dft_data = goertzel(y,freq_indices);<span class="comment">%goertzel(y,freq_indices); general_shortened</span>
+0082                 instances(i,:) = abs(dft_data) ./ length(y);
+0083                 labels(i,1) = floor(GT.trials{i}.label);
+0084             <span class="keyword">end</span>
+0085             GT.avgTime = toc/numTrials;
+0086             GT.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+0087             GT.pff = GT.nfft;
+0088         <span class="keyword">end</span>
+0089         
+0090         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(GT)</a>
+0091             configInfo = sprintf(<span class="string">'Goertzel\tchannel:%d\tseconds:%d\tfreq range:%.3f to %.3f'</span>,GT.channel,GT.seconds,GT.nfft(1),GT.nfft(end));
+0092         <span class="keyword">end</span>
+0093         
+0094         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(GT)</a>
+0095             time = GT.avgTime;
+0096         <span class="keyword">end</span>
+0097     <span class="keyword">end</span>
+0098    
+0099 <span class="keyword">end</span>
+0100</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.m b/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.m
new file mode 100644
index 0000000..09e61a4
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.m
@@ -0,0 +1,100 @@
+classdef Goertzel < eegtoolkit.featextraction.FeatureExtractionBase
+%Computes the psd using the welch method
+%Usage:
+%   session = eegtoolkit.util.Session();
+%   session.loadSubject(1);
+%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);
+%Specify the channel to be used (default = 126)
+%   pwt.channel = 150;
+%Specify the number of seconds to be used (default = 0, use all signal)
+%   pwt.seconds = 3;
+%Specify the nfft parameter (default = 512, computes 257 features)
+%   pwt.nfft = 512;
+%Transform the signal
+%   pwt.transform();
+    properties (Access = public)
+        channel;
+        seconds;
+        nfft;
+        pff;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function GT = Goertzel(trials, seconds, channel, nfft)
+%             if ~iscell(trials)
+%                 error('trials must be cell array of Trial object');
+%             end
+            if nargin == 0
+                GT.trials = {};
+                GT.seconds = 0;
+                GT.channel = 1;
+                GT.nfft = 512;
+            elseif nargin == 1
+                GT.trials = trials;
+                GT.seconds = 0;
+                GT.channel = 1;
+                GT.nfft = 512;
+            elseif nargin == 2
+                GT.trials = trials;
+                GT.channel = 1;
+                GT.seconds = seconds;
+                GT.nfft = 512;
+            elseif nargin == 3
+                GT.trials = trials;
+                GT.channel = channel;
+                GT.seconds = seconds;
+                GT.nfft = 512;
+            elseif nargin == 4
+                GT.trials = trials;
+                GT.channel = channel;
+                GT.seconds = seconds;
+                GT.nfft = nfft;
+            else
+%                 error('invalid number of arguments');
+            end
+        end
+        
+        function extract(GT)
+           
+            numFeatures = length(GT.nfft);
+            numTrials = length(GT.trials);
+            instances = zeros(numTrials, numFeatures);
+            labels = zeros(numTrials,1);
+%             PWT.instances = zeros(numTrials, numFeatures);
+%             PWT.labels = zeros(numTrials,1);
+            tic;
+            for i=1:numTrials
+                numsamples = GT.trials{i}.samplingRate * GT.seconds;
+                if(numsamples == 0)
+                    y = GT.trials{i}.signal(GT.channel,:);
+                else
+                    y = GT.trials{i}.signal(GT.channel, 1:numsamples);
+                end
+%                 N = (length(y)+1)/2;
+%                 f = (PWT.trials{i}.samplingRate/2)/N*(0:N-1);
+%                 indxs = find(f>1.2e3 & f<1.3e3);
+%                 X = goertzel(x,indxs);
+                freq_indices = round(GT.nfft/GT.trials{i}.samplingRate*length(y)) + 1;
+%                 ff = [0:1/512:1/2]*250;
+%                 freq_indices = round(ff/PWT.trials{i}.samplingRate*length(y))+1
+                dft_data = goertzel(y,freq_indices);%goertzel(y,freq_indices); general_shortened              
+                instances(i,:) = abs(dft_data) ./ length(y);
+                labels(i,1) = floor(GT.trials{i}.label);
+            end
+            GT.avgTime = toc/numTrials;
+            GT.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+            GT.pff = GT.nfft;
+        end
+        
+        function configInfo = getConfigInfo(GT)
+            configInfo = sprintf('Goertzel\tchannel:%d\tseconds:%d\tfreq range:%.3f to %.3f',GT.channel,GT.seconds,GT.nfft(1),GT.nfft(end));
+        end
+        
+        function time = getTime(GT)
+            time = GT.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.dot b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.dot
new file mode 100644
index 0000000..6759e88
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Goertzel -> Goertzel;
+
+  Goertzel [URL="Goertzel.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html
new file mode 100644
index 0000000..04a3c86
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@Goertzel">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@Goertzel">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Goertzel.html" title="Goertzel" alt="" coords="113,29,111,22,103,15,91,10,76,7,59,5,42,7,27,10,14,15,7,22,4,29,7,37,14,43,27,49,42,52,59,53,76,52,91,49,103,43,111,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.map b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.map
new file mode 100644
index 0000000..c134b8a
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="Goertzel.html" title="Goertzel" alt="" coords="113,29,111,22,103,15,91,10,76,7,59,5,42,7,27,10,14,15,7,22,4,29,7,37,14,43,27,49,42,52,59,53,76,52,91,49,103,43,111,37">
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.png b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/index.html b/doc/+eegtoolkit/+featextraction/@Goertzel/index.html
new file mode 100644
index 0000000..a9985e3
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@Goertzel</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@Goertzel">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@Goertzel">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@Goertzel</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Goertzel.html">Goertzel</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html
new file mode 100644
index 0000000..a32cc8c
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html
@@ -0,0 +1,77 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of L1MCCA</title>
+  <meta name="keywords" content="L1MCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@L1MCCA</a> &gt; L1MCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>L1MCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="../../../+eegtoolkit/+classification/@L1MCCA/L1MCCA.html" class="code" title="">L1MCCA</a>	</li><li><a href="L1MCCA.html" class="code" title="">L1MCCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="../../../+eegtoolkit/+classification/@L1MCCA/L1MCCA.html" class="code" title="">L1MCCA</a>	</li><li><a href="L1MCCA.html" class="code" title="">L1MCCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function L1MCCA = L1MCCA()</a></li><li><a href="#_sub2" class="code">function extract(L1MCCA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(L1MCCA)</a></li><li><a href="#_sub4" class="code">function time = getTime(L1MCCA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="L1MCCA.m">L1MCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="L1MCCA.html" class="code" title="">L1MCCA</a> &lt; eegtoolkit.featextraction.PSDExtractionBase<span class="comment">%FeatureExtractionBase</span>
+0002     <span class="comment">%</span>
+0003     <span class="comment">% works only on our datasets, for other datasets needs modifications</span>
+0004     <span class="comment">%</span>
+0005     properties (Access = public)
+0006         channel;
+0007         avgTime;
+0008         stimulus_freqs;
+0009         FreqSamp;
+0010         NumHarm;
+0011     <span class="keyword">end</span>
+0012     methods (Access = public)
+0013         <a name="_sub0" href="#_subfunctions" class="code">function L1MCCA = L1MCCA()</a>
+0014         <span class="keyword">end</span>
+0015         
+0016         <a name="_sub1" href="#_subfunctions" class="code">function extract(L1MCCA)</a>
+0017             L1MCCA.instanceSet = eegtoolkit.util.L1MCCAInstanceSet(L1MCCA.trials);
+0018         <span class="keyword">end</span>
+0019         
+0020         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(L1MCCA)</a>
+0021             configInfo = sprintf(<span class="string">'L1MCCA'</span>);
+0022         <span class="keyword">end</span>
+0023         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(L1MCCA)</a>
+0024             time = 0;
+0025         <span class="keyword">end</span>
+0026     <span class="keyword">end</span>
+0027 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.m b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.m
new file mode 100644
index 0000000..ed3a795
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.m
@@ -0,0 +1,27 @@
+classdef L1MCCA < eegtoolkit.featextraction.PSDExtractionBase%FeatureExtractionBase
+    %
+    % works only on our datasets, for other datasets needs modifications
+    %
+    properties (Access = public)
+        channel;
+        avgTime;
+        stimulus_freqs;
+        FreqSamp;
+        NumHarm;
+    end
+    methods (Access = public)
+        function L1MCCA = L1MCCA()
+        end
+        
+        function extract(L1MCCA)
+            L1MCCA.instanceSet = eegtoolkit.util.L1MCCAInstanceSet(L1MCCA.trials);
+        end
+        
+        function configInfo = getConfigInfo(L1MCCA)
+            configInfo = sprintf('L1MCCA');
+        end
+        function time = getTime(L1MCCA)
+            time = 0;
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.dot b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.dot
new file mode 100644
index 0000000..5dff22f
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  L1MCCA -> L1MCCA;
+
+  L1MCCA [URL="L1MCCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html
new file mode 100644
index 0000000..f1e9037
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@L1MCCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@L1MCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="L1MCCA.html" title="L1MCCA" alt="" coords="129,29,126,22,117,15,103,10,86,7,67,5,47,7,30,10,16,15,7,22,4,29,7,37,16,43,30,49,47,52,67,53,86,52,103,49,117,43,126,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.map b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.map
new file mode 100644
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--- /dev/null
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diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html
new file mode 100644
index 0000000..73d7594
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@L1MCCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@L1MCCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@L1MCCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@L1MCCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="L1MCCA.html">L1MCCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html
new file mode 100644
index 0000000..ad43195
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html
@@ -0,0 +1,114 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of MLR_Transf</title>
+  <meta name="keywords" content="MLR_Transf">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@MLR_Transf</a> &gt; MLR_Transf.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>MLR_Transf
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLR_Transf.html" class="code" title="">MLR_Transf</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="MLR_Transf.html" class="code" title="">MLR_Transf</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function PWT = MLR_Transf(chns)</a></li><li><a href="#_sub2" class="code">function extract(PWT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(PWT)</a></li><li><a href="#_sub4" class="code">function time = getTime(PWT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="MLR_Transf.m">MLR_Transf.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="MLR_Transf.html" class="code" title="">MLR_Transf</a> &lt; eegtoolkit.featextraction.PSDExtractionBase<span class="comment">%FeatureExtractionBase</span>
+0002     <span class="comment">%Computes the psd using the welch method</span>
+0003     <span class="comment">%Usage:</span>
+0004     <span class="comment">%   session = eegtoolkit.util.Session();</span>
+0005     <span class="comment">%   session.loadSubject(1);</span>
+0006     <span class="comment">%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);</span>
+0007     <span class="comment">%Specify the channel to be used (default = 126)</span>
+0008     <span class="comment">%   pwt.channel = 150;</span>
+0009     <span class="comment">%Specify the number of seconds to be used (default = 0, use all signal)</span>
+0010     <span class="comment">%   pwt.seconds = 3;</span>
+0011     <span class="comment">%Specify the nfft parameter (default = 512, computes 257 features)</span>
+0012     <span class="comment">%   pwt.nfft = 512;</span>
+0013     <span class="comment">%Transform the signal</span>
+0014     <span class="comment">%   pwt.transform();</span>
+0015     properties (Access = public)
+0016         channel;
+0017         avgTime;
+0018     <span class="keyword">end</span>
+0019     methods (Access = public)
+0020         <a name="_sub0" href="#_subfunctions" class="code">function PWT = MLR_Transf(chns)</a>
+0021             <span class="keyword">if</span> nargin == 1
+0022                 PWT.trials = {};
+0023                 PWT.channel = [1:length(chns)];
+0024             <span class="keyword">else</span>
+0025                 error(<span class="string">'invalid number of arguments'</span>);
+0026             <span class="keyword">end</span>
+0027         <span class="keyword">end</span>
+0028         
+0029         <a name="_sub1" href="#_subfunctions" class="code">function extract(PWT)</a>
+0030             
+0031             numTrials = length(PWT.trials);
+0032             [m n]=size(PWT.trials{1}.signal(PWT.channel,:));
+0033             data = zeros(m,n,numTrials);
+0034             labels = zeros(numTrials,1);
+0035             
+0036             <span class="keyword">for</span> i = 1 : numTrials   <span class="comment">%</span>
+0037                 <span class="keyword">for</span> j=1:m
+0038                     data(j,:,i) = PWT.trials{i}.signal(j,:);<span class="comment">%data(j,:,i)./norm(data(j,:,i));</span>
+0039                     data(j,:,i) = (data(j,:,i) - mean(data(j,:,i)))./std(data(j,:,i));
+0040 <span class="comment">%                     data(j,:,i) = data(j,:,i)./norm(data(j,:,i));</span>
+0041                 <span class="keyword">end</span><span class="comment">%</span>
+0042                 labels(i) = floor(PWT.trials{i}.label);
+0043             <span class="keyword">end</span>
+0044             <span class="comment">%data= reshape(data,m*n,size(data,3));</span>
+0045             <span class="keyword">for</span> i=1:numTrials
+0046                 newData(i,:) = [data(1,:,i) data(2,:,i)];
+0047             <span class="keyword">end</span>
+0048             <span class="comment">%             MeanTrainData=mean(data,2);</span>
+0049             <span class="comment">%             data=data-repmat(MeanTrainData,1,numTrials);</span>
+0050             data = newData;
+0051             PWT.instanceSet = eegtoolkit.util.InstanceSet(data, labels);
+0052         <span class="keyword">end</span>
+0053         
+0054         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(PWT)</a>
+0055             configInfo = sprintf(<span class="string">'MLR_Transf_rawdata'</span>);
+0056         <span class="keyword">end</span>
+0057         
+0058         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(PWT)</a>
+0059             time = PWT.avgTime;
+0060         <span class="keyword">end</span>
+0061     <span class="keyword">end</span>
+0062     
+0063 <span class="keyword">end</span>
+0064</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.m b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.m
new file mode 100644
index 0000000..4c1c6e5
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.m
@@ -0,0 +1,64 @@
+classdef MLR_Transf < eegtoolkit.featextraction.PSDExtractionBase%FeatureExtractionBase
+    %Computes the psd using the welch method
+    %Usage:
+    %   session = eegtoolkit.util.Session();
+    %   session.loadSubject(1);
+    %   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);
+    %Specify the channel to be used (default = 126)
+    %   pwt.channel = 150;
+    %Specify the number of seconds to be used (default = 0, use all signal)
+    %   pwt.seconds = 3;
+    %Specify the nfft parameter (default = 512, computes 257 features)
+    %   pwt.nfft = 512;
+    %Transform the signal
+    %   pwt.transform();
+    properties (Access = public)
+        channel;
+        avgTime;
+    end
+    methods (Access = public)
+        function PWT = MLR_Transf(chns)
+            if nargin == 1
+                PWT.trials = {};
+                PWT.channel = [1:length(chns)];
+            else
+                error('invalid number of arguments');
+            end
+        end
+        
+        function extract(PWT)
+            
+            numTrials = length(PWT.trials);
+            [m n]=size(PWT.trials{1}.signal(PWT.channel,:));
+            data = zeros(m,n,numTrials);
+            labels = zeros(numTrials,1);
+            
+            for i = 1 : numTrials   %
+                for j=1:m
+                    data(j,:,i) = PWT.trials{i}.signal(j,:);%data(j,:,i)./norm(data(j,:,i));
+                    data(j,:,i) = (data(j,:,i) - mean(data(j,:,i)))./std(data(j,:,i));
+%                     data(j,:,i) = data(j,:,i)./norm(data(j,:,i));
+                end%
+                labels(i) = floor(PWT.trials{i}.label);
+            end
+            %data= reshape(data,m*n,size(data,3));
+            for i=1:numTrials
+                newData(i,:) = [data(1,:,i) data(2,:,i)];
+            end
+            %             MeanTrainData=mean(data,2);
+            %             data=data-repmat(MeanTrainData,1,numTrials);
+            data = newData;
+            PWT.instanceSet = eegtoolkit.util.InstanceSet(data, labels);
+        end
+        
+        function configInfo = getConfigInfo(PWT)
+            configInfo = sprintf('MLR_Transf_rawdata');
+        end
+        
+        function time = getTime(PWT)
+            time = PWT.avgTime;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.dot b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.dot
new file mode 100644
index 0000000..3031a6a
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  MLR_Transf -> MLR_Transf;
+
+  MLR_Transf [URL="MLR_Transf.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html
new file mode 100644
index 0000000..12815ea
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@MLR_Transf">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@MLR_Transf">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="MLR_Transf.html" title="MLR_Transf" alt="" coords="158,29,155,22,144,15,127,10,105,7,81,5,57,7,36,10,19,15,8,22,4,29,8,37,19,43,36,49,57,52,81,53,105,52,127,49,144,43,155,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.map b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html
new file mode 100644
index 0000000..64166c1
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@MLR_Transf</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@MLR_Transf">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@MLR_Transf">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@MLR_Transf</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="MLR_Transf.html">MLR_Transf</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html
new file mode 100644
index 0000000..88fe395
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html
@@ -0,0 +1,55 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PSDExtractionBase</title>
+  <meta name="keywords" content="PSDExtractionBase">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PSDExtractionBase</a> &gt; PSDExtractionBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PSDExtractionBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PSDExtractionBase.html" class="code" title="">PSDExtractionBase</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PSDExtractionBase.html" class="code" title="">PSDExtractionBase</a>	</li></ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PSDExtractionBase.m">PSDExtractionBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef (Abstract) <a href="PSDExtractionBase.html" class="code" title="">PSDExtractionBase</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     <span class="comment">%Base class for a feature transformer based on power spectral density</span>
+0003     <span class="comment">%estimates</span>
+0004     properties (Access = public)
+0005         pff; <span class="comment">% The frequencies of the spectrum</span>
+0006     <span class="keyword">end</span>
+0007 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.m b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.m
new file mode 100644
index 0000000..d2a71a7
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.m
@@ -0,0 +1,7 @@
+classdef (Abstract) PSDExtractionBase < eegtoolkit.featextraction.FeatureExtractionBase
+    %Base class for a feature transformer based on power spectral density
+    %estimates
+    properties (Access = public)
+        pff; % The frequencies of the spectrum
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.dot b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.dot
new file mode 100644
index 0000000..246d58e
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PSDExtractionBase -> PSDExtractionBase;
+
+  PSDExtractionBase [URL="PSDExtractionBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html
new file mode 100644
index 0000000..6467381
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PSDExtractionBase.html" title="PSDExtractionBase" alt="" coords="219,29,214,22,199,15,175,10,145,7,112,5,79,7,49,10,25,15,10,22,5,29,10,37,25,43,49,49,79,52,112,53,145,52,175,49,199,43,214,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.map b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.map
new file mode 100644
index 0000000..5c6e47e
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.png b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.png
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diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/index.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/index.html
new file mode 100644
index 0000000..bdf93e0
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@PSDExtractionBase</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PSDExtractionBase.html">PSDExtractionBase</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html
new file mode 100644
index 0000000..07f77f4
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html
@@ -0,0 +1,167 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PWelch</title>
+  <meta name="keywords" content="PWelch">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PWelch</a> &gt; PWelch.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PWelch
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PWelch.html" class="code" title="">PWelch</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PWelch.html" class="code" title="">PWelch</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function PW = PWelch(trials, seconds, channel, nfft)</a></li><li><a href="#_sub2" class="code">function extract(PW)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(PW)</a></li><li><a href="#_sub4" class="code">function time = getTime(PW)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PWelch.m">PWelch.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="PWelch.html" class="code" title="">PWelch</a> &lt; eegtoolkit.featextraction.PSDExtractionBase
+0002 <span class="comment">%Computes the psd using the welch method</span>
+0003 <span class="comment">%Usage:</span>
+0004 <span class="comment">%   session = eegtoolkit.util.Session();</span>
+0005 <span class="comment">%   session.loadSubject(1);</span>
+0006 <span class="comment">%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);</span>
+0007 <span class="comment">%Specify the channel to be used (default = 126)</span>
+0008 <span class="comment">%   pwt.channel = 150;</span>
+0009 <span class="comment">%Specify the number of seconds to be used (default = 0, use all signal)</span>
+0010 <span class="comment">%   pwt.seconds = 3;</span>
+0011 <span class="comment">%Specify the nfft parameter (default = 512, computes 257 features)</span>
+0012 <span class="comment">%   pwt.nfft = 512;</span>
+0013 <span class="comment">%Transform the signal</span>
+0014 <span class="comment">%   pwt.transform();</span>
+0015     properties (Access = public)
+0016         channel;
+0017         seconds;
+0018         nfft;
+0019         avgTime;
+0020     <span class="keyword">end</span>
+0021     
+0022     methods (Access = public)
+0023         <a name="_sub0" href="#_subfunctions" class="code">function PW = PWelch(trials, seconds, channel, nfft)</a>
+0024 <span class="comment">%             if ~iscell(trials)</span>
+0025 <span class="comment">%                 error('trials must be cell array of Trial object');</span>
+0026 <span class="comment">%             end</span>
+0027             <span class="keyword">if</span> nargin == 0
+0028                 PW.trials = {};
+0029                 PW.seconds = 0;
+0030                 PW.channel = 1;
+0031                 PW.nfft = 512;
+0032             <span class="keyword">elseif</span> nargin == 1
+0033                 PW.trials = trials;
+0034                 PW.seconds = 0;
+0035                 PW.channel = 1;
+0036                 PW.nfft = 512;
+0037             <span class="keyword">elseif</span> nargin == 2
+0038                 PW.trials = trials;
+0039                 PW.channel = 1;
+0040                 PW.seconds = seconds;
+0041                 PW.nfft = 512;
+0042             <span class="keyword">elseif</span> nargin == 3
+0043                 PW.trials = trials;
+0044                 PW.channel = channel;
+0045                 PW.seconds = seconds;
+0046                 PW.nfft = 512;
+0047             <span class="keyword">elseif</span> nargin == 4
+0048                 PW.trials = trials;
+0049                 PW.channel = channel;
+0050                 PW.seconds = seconds;
+0051                 PW.nfft = nfft;
+0052             <span class="keyword">else</span>
+0053 <span class="comment">%                 error('invalid number of arguments');</span>
+0054             <span class="keyword">end</span>
+0055         <span class="keyword">end</span>
+0056         
+0057         <a name="_sub1" href="#_subfunctions" class="code">function extract(PW)</a>
+0058             <span class="keyword">if</span> length(PW.nfft)==1
+0059                 numFeatures = PW.nfft/2+1;
+0060             <span class="keyword">else</span>
+0061                 numFeatures = length(PW.nfft);
+0062             <span class="keyword">end</span>
+0063             numTrials = length(PW.trials);
+0064             instances = zeros(numTrials, numFeatures);
+0065             labels = zeros(numTrials,1);
+0066 <span class="comment">%             PWT.instances = zeros(numTrials, numFeatures);</span>
+0067 <span class="comment">%             PWT.labels = zeros(numTrials,1);</span>
+0068             tic;
+0069             <span class="keyword">for</span> i=1:numTrials
+0070                 <span class="keyword">if</span> length(PW.seconds) == 1
+0071                     numsamples = PW.trials{i}.samplingRate * PW.seconds;
+0072                     <span class="keyword">if</span>(numsamples == 0)
+0073                         y = PW.trials{i}.signal(PW.channel,:);
+0074                     <span class="keyword">else</span>
+0075                         y = PW.trials{i}.signal(PW.channel, 1:numsamples);
+0076                     <span class="keyword">end</span>
+0077                 <span class="keyword">elseif</span> length(PW.seconds) == 2
+0078                     sampleA = PW.trials{i}.samplingRate*PW.seconds(1) +1;
+0079                     sampleB = PW.trials{i}.samplingRate*PW.seconds(2);
+0080                     y = PW.trials{i}.signal(PW.channel, sampleA:sampleB);
+0081                 <span class="keyword">else</span> 
+0082                     error(<span class="string">'invalid seconds parameter'</span>);
+0083                 <span class="keyword">end</span>
+0084                 <span class="keyword">if</span> isa(PW.filter,<span class="string">'dfilt.df2sos'</span>) || isa(PW.filter,<span class="string">'dfilt.df2'</span>)
+0085                     y = filter(PW.filter,y);
+0086                 <span class="keyword">elseif</span> isa(PW.filter,<span class="string">'dfilt.dffir'</span>)
+0087                     y = filtfilt(PW.filter.Numerator,1,y);
+0088                 <span class="keyword">end</span>
+0089                 <span class="keyword">if</span> length(PW.nfft&gt;1)
+0090                     [pxx, pff]=pwelch(y,[],[],PW.nfft,PW.trials{i}.samplingRate);
+0091                 <span class="keyword">else</span>
+0092                     [pxx, pff]=pwelch(y,[],[],PW.nfft,PW.trials{i}.samplingRate,<span class="string">'onesided'</span>);
+0093                 <span class="keyword">end</span>
+0094                 instances(i,:) = pxx;
+0095                 labels(i,1) = floor(PW.trials{i}.label);
+0096             <span class="keyword">end</span>
+0097             total = toc;
+0098             PW.avgTime = total/numTrials;
+0099             PW.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+0100             PW.pff = pff;
+0101         <span class="keyword">end</span>
+0102         
+0103         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(PW)</a>
+0104             <span class="keyword">if</span> length(PW.nfft)&gt;1
+0105                 configInfo = sprintf(<span class="string">'PWelch\tchannel:%d\tseconds:%d\t freq range:%.3f to %.3f'</span>,PW.channel,PW.seconds,PW.nfft(1),PW.nfft(end));
+0106             <span class="keyword">else</span>
+0107                 configInfo = sprintf(<span class="string">'PWelch\tchannel:%d\tseconds:%d\tnfft:%d'</span>,PW.channel,PW.seconds,PW.nfft);
+0108             <span class="keyword">end</span>
+0109         <span class="keyword">end</span>
+0110         
+0111         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(PW)</a>
+0112             time = PW.avgTime;
+0113         <span class="keyword">end</span>
+0114     <span class="keyword">end</span>
+0115    
+0116 <span class="keyword">end</span>
+0117</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.m b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.m
new file mode 100644
index 0000000..0dc4a92
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.m
@@ -0,0 +1,117 @@
+classdef PWelch < eegtoolkit.featextraction.PSDExtractionBase
+%Computes the psd using the welch method
+%Usage:
+%   session = eegtoolkit.util.Session();
+%   session.loadSubject(1);
+%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);
+%Specify the channel to be used (default = 126)
+%   pwt.channel = 150;
+%Specify the number of seconds to be used (default = 0, use all signal)
+%   pwt.seconds = 3;
+%Specify the nfft parameter (default = 512, computes 257 features)
+%   pwt.nfft = 512;
+%Transform the signal
+%   pwt.transform();
+    properties (Access = public)
+        channel;
+        seconds;
+        nfft;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function PW = PWelch(trials, seconds, channel, nfft)
+%             if ~iscell(trials)
+%                 error('trials must be cell array of Trial object');
+%             end
+            if nargin == 0
+                PW.trials = {};
+                PW.seconds = 0;
+                PW.channel = 1;
+                PW.nfft = 512;
+            elseif nargin == 1
+                PW.trials = trials;
+                PW.seconds = 0;
+                PW.channel = 1;
+                PW.nfft = 512;
+            elseif nargin == 2
+                PW.trials = trials;
+                PW.channel = 1;
+                PW.seconds = seconds;
+                PW.nfft = 512;
+            elseif nargin == 3
+                PW.trials = trials;
+                PW.channel = channel;
+                PW.seconds = seconds;
+                PW.nfft = 512;
+            elseif nargin == 4
+                PW.trials = trials;
+                PW.channel = channel;
+                PW.seconds = seconds;
+                PW.nfft = nfft;
+            else
+%                 error('invalid number of arguments');
+            end
+        end
+        
+        function extract(PW)
+            if length(PW.nfft)==1
+                numFeatures = PW.nfft/2+1;
+            else
+                numFeatures = length(PW.nfft);
+            end
+            numTrials = length(PW.trials);
+            instances = zeros(numTrials, numFeatures);
+            labels = zeros(numTrials,1);
+%             PWT.instances = zeros(numTrials, numFeatures);
+%             PWT.labels = zeros(numTrials,1);
+            tic;
+            for i=1:numTrials
+                if length(PW.seconds) == 1
+                    numsamples = PW.trials{i}.samplingRate * PW.seconds;
+                    if(numsamples == 0)
+                        y = PW.trials{i}.signal(PW.channel,:);
+                    else
+                        y = PW.trials{i}.signal(PW.channel, 1:numsamples);
+                    end
+                elseif length(PW.seconds) == 2
+                    sampleA = PW.trials{i}.samplingRate*PW.seconds(1) +1;
+                    sampleB = PW.trials{i}.samplingRate*PW.seconds(2);
+                    y = PW.trials{i}.signal(PW.channel, sampleA:sampleB);
+                else 
+                    error('invalid seconds parameter');
+                end
+                if isa(PW.filter,'dfilt.df2sos') || isa(PW.filter,'dfilt.df2')
+                    y = filter(PW.filter,y);
+                elseif isa(PW.filter,'dfilt.dffir')
+                    y = filtfilt(PW.filter.Numerator,1,y);
+                end
+                if length(PW.nfft>1)
+                    [pxx, pff]=pwelch(y,[],[],PW.nfft,PW.trials{i}.samplingRate);
+                else
+                    [pxx, pff]=pwelch(y,[],[],PW.nfft,PW.trials{i}.samplingRate,'onesided');
+                end
+                instances(i,:) = pxx;
+                labels(i,1) = floor(PW.trials{i}.label);
+            end
+            total = toc;
+            PW.avgTime = total/numTrials;
+            PW.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+            PW.pff = pff;
+        end
+        
+        function configInfo = getConfigInfo(PW)
+            if length(PW.nfft)>1
+                configInfo = sprintf('PWelch\tchannel:%d\tseconds:%d\t freq range:%.3f to %.3f',PW.channel,PW.seconds,PW.nfft(1),PW.nfft(end));
+            else
+                configInfo = sprintf('PWelch\tchannel:%d\tseconds:%d\tnfft:%d',PW.channel,PW.seconds,PW.nfft);
+            end
+        end
+        
+        function time = getTime(PW)
+            time = PW.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/graph.dot b/doc/+eegtoolkit/+featextraction/@PWelch/graph.dot
new file mode 100644
index 0000000..806a74c
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PWelch -> PWelch;
+
+  PWelch [URL="PWelch.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/graph.html b/doc/+eegtoolkit/+featextraction/@PWelch/graph.html
new file mode 100644
index 0000000..9d3d176
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelch</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@PWelch">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PWelch">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelch</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PWelch" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PWelch.html" title="PWelch" alt="" coords="108,29,105,22,98,15,87,10,72,7,56,5,40,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,40,52,56,53,72,52,87,49,98,43,105,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/graph.map b/doc/+eegtoolkit/+featextraction/@PWelch/graph.map
new file mode 100644
index 0000000..de91879
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="PWelch.html" title="PWelch" alt="" coords="108,29,105,22,98,15,87,10,72,7,56,5,40,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,40,52,56,53,72,52,87,49,98,43,105,37">
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/index.html b/doc/+eegtoolkit/+featextraction/@PWelch/index.html
new file mode 100644
index 0000000..e8b3357
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@PWelch</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PWelch">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PWelch">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
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+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@PWelch</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PWelch.html">PWelch</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html
new file mode 100644
index 0000000..9619064
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html
@@ -0,0 +1,183 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PWelchExperimental</title>
+  <meta name="keywords" content="PWelchExperimental">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PWelchExperimental</a> &gt; PWelchExperimental.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PWelchExperimental
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PWelchExperimental.html" class="code" title="">PWelchExperimental</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PWelchExperimental.html" class="code" title="">PWelchExperimental</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function PWT = PWelchExperimental(trials, seconds, channel, nfft,win_len,over_len)</a></li><li><a href="#_sub2" class="code">function extract(PWT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(PWT)</a></li><li><a href="#_sub4" class="code">function time = getTime(PWT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PWelchExperimental.m">PWelchExperimental.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="PWelchExperimental.html" class="code" title="">PWelchExperimental</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002 <span class="comment">%Computes the psd using the welch method</span>
+0003 <span class="comment">%Usage:</span>
+0004 <span class="comment">%   session = eegtoolkit.util.Session();</span>
+0005 <span class="comment">%   session.loadSubject(1);</span>
+0006 <span class="comment">%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);</span>
+0007 <span class="comment">%Specify the channel to be used (default = 126)</span>
+0008 <span class="comment">%   pwt.channel = 150;</span>
+0009 <span class="comment">%Specify the number of seconds to be used (default = 0, use all signal)</span>
+0010 <span class="comment">%   pwt.seconds = 3;</span>
+0011 <span class="comment">%Specify the nfft parameter (default = 512, computes 257 features)</span>
+0012 <span class="comment">%   pwt.nfft = 512;</span>
+0013 <span class="comment">%Transform the signal</span>
+0014 <span class="comment">%   pwt.transform();</span>
+0015     properties (Access = public)
+0016         channel;
+0017         seconds;
+0018         nfft;
+0019         pff;
+0020         win_len;
+0021         over_len;
+0022         avgTime;
+0023     <span class="keyword">end</span>
+0024     
+0025     methods (Access = public)
+0026         <a name="_sub0" href="#_subfunctions" class="code">function PWT = PWelchExperimental(trials, seconds, channel, nfft,win_len,over_len)</a>
+0027 <span class="comment">%             if ~iscell(trials)</span>
+0028 <span class="comment">%                 error('trials must be cell array of Trial object');</span>
+0029 <span class="comment">%             end</span>
+0030             <span class="keyword">if</span> nargin == 0
+0031                 PWT.trials = {};
+0032                 PWT.seconds = 0;
+0033                 PWT.channel = 1;
+0034                 PWT.nfft = 512;
+0035                 PWT.win_len=[];
+0036                 PWT.over_len=[];
+0037             <span class="keyword">elseif</span> nargin == 1
+0038                 PWT.trials = trials;
+0039                 PWT.seconds = 0;
+0040                 PWT.channel = 1;
+0041                 PWT.nfft = 512;
+0042                 PWT.win_len=[];
+0043                 PWT.over_len=[];
+0044             <span class="keyword">elseif</span> nargin == 2
+0045                 PWT.trials = trials;
+0046                 PWT.channel = 1;
+0047                 PWT.seconds = seconds;
+0048                 PWT.nfft = 512;
+0049                 PWT.win_len=[];
+0050                 PWT.over_len=[];
+0051             <span class="keyword">elseif</span> nargin == 3
+0052                 PWT.trials = trials;
+0053                 PWT.channel = channel;
+0054                 PWT.seconds = seconds;
+0055                 PWT.nfft = 512;
+0056                 PWT.win_len=[];
+0057                 PWT.over_len=[];
+0058             <span class="keyword">elseif</span> nargin == 4
+0059                 PWT.trials = trials;
+0060                 PWT.channel = channel;
+0061                 PWT.seconds = seconds;
+0062                 PWT.nfft = nfft;
+0063                 PWT.win_len=[];
+0064                 PWT.over_len=[];
+0065             <span class="keyword">elseif</span> nargin == 5
+0066                 PWT.trials = trials;
+0067                 PWT.channel = channel;
+0068                 PWT.seconds = seconds;
+0069                 PWT.nfft = nfft;
+0070                 PWT.win_len=win_len;
+0071                 PWT.over_len=[];
+0072             <span class="keyword">elseif</span> nargin == 6
+0073                 PWT.trials = trials;
+0074                 PWT.channel = channel;
+0075                 PWT.seconds = seconds;
+0076                 PWT.nfft = nfft;
+0077                 PWT.win_len=win_len;
+0078                 PWT.over_len=over_len;
+0079             <span class="keyword">else</span>
+0080 <span class="comment">%                 error('invalid number of arguments');</span>
+0081             <span class="keyword">end</span>
+0082         <span class="keyword">end</span>
+0083         
+0084         <a name="_sub1" href="#_subfunctions" class="code">function extract(PWT)</a>
+0085             <span class="keyword">if</span> length(PWT.nfft)==1
+0086                 numFeatures = PWT.nfft/2+1;
+0087             <span class="keyword">else</span>
+0088                 numFeatures = length(PWT.nfft);
+0089             <span class="keyword">end</span>
+0090             numTrials = length(PWT.trials);
+0091             instances = zeros(numTrials, numFeatures);
+0092             labels = zeros(numTrials,1);
+0093 <span class="comment">%             PWT.instances = zeros(numTrials, numFeatures);</span>
+0094 <span class="comment">%             PWT.labels = zeros(numTrials,1);</span>
+0095             tic;
+0096             <span class="keyword">for</span> i=1:numTrials
+0097                 numsamples = PWT.trials{i}.samplingRate * PWT.seconds;
+0098                 <span class="keyword">if</span>(numsamples == 0)
+0099                     y = PWT.trials{i}.signal(PWT.channel,:);
+0100                 <span class="keyword">else</span>
+0101                     y = PWT.trials{i}.signal(PWT.channel, 1:numsamples);
+0102                 <span class="keyword">end</span>
+0103 <span class="comment">%                 if length(PWT.nfft&gt;1)</span>
+0104 <span class="comment">%                     [pxx, pff]=pwelch(y,[],[],PWT.nfft,PWT.trials{i}.samplingRate);</span>
+0105 <span class="comment">%                 else</span>
+0106                     [pxx, pff]=pwelch(y,PWT.win_len,round(PWT.over_len*PWT.win_len),PWT.nfft,PWT.trials{i}.samplingRate,<span class="string">'onesided'</span>);
+0107 <span class="comment">%                 end</span>
+0108                 <span class="comment">%xv = [1 -2 1 zeros(1,length(pxx)-3)];</span>
+0109 <span class="comment">%                 xv = [1/5 1/5 1/5 1/5 1/5 zeros(1,length(pxx)-5)];</span>
+0110 <span class="comment">%                 A = gallery('circul',xv);</span>
+0111                 instances(i,:) = pxx;
+0112                 labels(i,1) = floor(PWT.trials{i}.label);
+0113             <span class="keyword">end</span>
+0114             PWT.avgTime = toc/numTrials;
+0115             PWT.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+0116             PWT.pff = pff;
+0117         <span class="keyword">end</span>
+0118         
+0119         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(PWT)</a>
+0120             <span class="keyword">if</span> length(PWT.nfft)&gt;1
+0121                 configInfo = sprintf(<span class="string">'PWelchExperimental\tchannel:%d\tseconds:%d\t freq range:%.3f to %.3f'</span>,PWT.channel,PWT.seconds,PWT.nfft(1),PWT.nfft(end));
+0122             <span class="keyword">else</span>
+0123                 configInfo = sprintf(<span class="string">'PWelchExperimental\tchannel:%d\tseconds:%d\tnfft:%d'</span>,PWT.channel,PWT.seconds,PWT.nfft);
+0124             <span class="keyword">end</span>
+0125         <span class="keyword">end</span>
+0126         
+0127         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(PWT)</a>
+0128             time = PWT.avgTime;
+0129         <span class="keyword">end</span>
+0130     <span class="keyword">end</span>
+0131    
+0132 <span class="keyword">end</span>
+0133</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.m b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.m
new file mode 100644
index 0000000..d01cb0e
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.m
@@ -0,0 +1,133 @@
+classdef PWelchExperimental < eegtoolkit.featextraction.FeatureExtractionBase
+%Computes the psd using the welch method
+%Usage:
+%   session = eegtoolkit.util.Session();
+%   session.loadSubject(1);
+%   pwt = ssveptolkit.transform.PWelchTransformer(session.trials);
+%Specify the channel to be used (default = 126)
+%   pwt.channel = 150;
+%Specify the number of seconds to be used (default = 0, use all signal)
+%   pwt.seconds = 3;
+%Specify the nfft parameter (default = 512, computes 257 features)
+%   pwt.nfft = 512;
+%Transform the signal
+%   pwt.transform();
+    properties (Access = public)
+        channel;
+        seconds;
+        nfft;
+        pff;
+        win_len;
+        over_len;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function PWT = PWelchExperimental(trials, seconds, channel, nfft,win_len,over_len)
+%             if ~iscell(trials)
+%                 error('trials must be cell array of Trial object');
+%             end
+            if nargin == 0
+                PWT.trials = {};
+                PWT.seconds = 0;
+                PWT.channel = 1;
+                PWT.nfft = 512;
+                PWT.win_len=[];
+                PWT.over_len=[];
+            elseif nargin == 1
+                PWT.trials = trials;
+                PWT.seconds = 0;
+                PWT.channel = 1;
+                PWT.nfft = 512;
+                PWT.win_len=[];
+                PWT.over_len=[];
+            elseif nargin == 2
+                PWT.trials = trials;
+                PWT.channel = 1;
+                PWT.seconds = seconds;
+                PWT.nfft = 512;
+                PWT.win_len=[];
+                PWT.over_len=[];
+            elseif nargin == 3
+                PWT.trials = trials;
+                PWT.channel = channel;
+                PWT.seconds = seconds;
+                PWT.nfft = 512;
+                PWT.win_len=[];
+                PWT.over_len=[];
+            elseif nargin == 4
+                PWT.trials = trials;
+                PWT.channel = channel;
+                PWT.seconds = seconds;
+                PWT.nfft = nfft;
+                PWT.win_len=[];
+                PWT.over_len=[];
+            elseif nargin == 5
+                PWT.trials = trials;
+                PWT.channel = channel;
+                PWT.seconds = seconds;
+                PWT.nfft = nfft;
+                PWT.win_len=win_len;
+                PWT.over_len=[];
+            elseif nargin == 6
+                PWT.trials = trials;
+                PWT.channel = channel;
+                PWT.seconds = seconds;
+                PWT.nfft = nfft;
+                PWT.win_len=win_len;
+                PWT.over_len=over_len;
+            else
+%                 error('invalid number of arguments');
+            end
+        end
+        
+        function extract(PWT)
+            if length(PWT.nfft)==1
+                numFeatures = PWT.nfft/2+1;
+            else
+                numFeatures = length(PWT.nfft);
+            end
+            numTrials = length(PWT.trials);
+            instances = zeros(numTrials, numFeatures);
+            labels = zeros(numTrials,1);
+%             PWT.instances = zeros(numTrials, numFeatures);
+%             PWT.labels = zeros(numTrials,1);
+            tic;
+            for i=1:numTrials
+                numsamples = PWT.trials{i}.samplingRate * PWT.seconds;
+                if(numsamples == 0)
+                    y = PWT.trials{i}.signal(PWT.channel,:);
+                else
+                    y = PWT.trials{i}.signal(PWT.channel, 1:numsamples);
+                end
+%                 if length(PWT.nfft>1)
+%                     [pxx, pff]=pwelch(y,[],[],PWT.nfft,PWT.trials{i}.samplingRate);
+%                 else
+                    [pxx, pff]=pwelch(y,PWT.win_len,round(PWT.over_len*PWT.win_len),PWT.nfft,PWT.trials{i}.samplingRate,'onesided');
+%                 end
+                %xv = [1 -2 1 zeros(1,length(pxx)-3)];
+%                 xv = [1/5 1/5 1/5 1/5 1/5 zeros(1,length(pxx)-5)];
+%                 A = gallery('circul',xv);
+                instances(i,:) = pxx;
+                labels(i,1) = floor(PWT.trials{i}.label);
+            end
+            PWT.avgTime = toc/numTrials;
+            PWT.instanceSet = eegtoolkit.util.InstanceSet(instances, labels);
+            PWT.pff = pff;
+        end
+        
+        function configInfo = getConfigInfo(PWT)
+            if length(PWT.nfft)>1
+                configInfo = sprintf('PWelchExperimental\tchannel:%d\tseconds:%d\t freq range:%.3f to %.3f',PWT.channel,PWT.seconds,PWT.nfft(1),PWT.nfft(end));
+            else
+                configInfo = sprintf('PWelchExperimental\tchannel:%d\tseconds:%d\tnfft:%d',PWT.channel,PWT.seconds,PWT.nfft);
+            end
+        end
+        
+        function time = getTime(PWT)
+            time = PWT.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.dot b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.dot
new file mode 100644
index 0000000..335d08e
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PWelchExperimental -> PWelchExperimental;
+
+  PWelchExperimental [URL="PWelchExperimental.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html
new file mode 100644
index 0000000..2dff583
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelchExperimental</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@PWelchExperimental">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PWelchExperimental">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelchExperimental</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PWelchExperimental" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PWelchExperimental.html" title="PWelchExperimental" alt="" coords="237,29,232,22,215,15,190,10,157,7,121,5,85,7,53,10,27,15,11,22,5,29,11,37,27,43,53,49,85,52,121,53,157,52,190,49,215,43,232,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.map b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.map
new file mode 100644
index 0000000..16c5e9c
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="PWelchExperimental.html" title="PWelchExperimental" alt="" coords="237,29,232,22,215,15,190,10,157,7,121,5,85,7,53,10,27,15,11,22,5,29,11,37,27,43,53,49,85,52,121,53,157,52,190,49,215,43,232,37">
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.png b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.png
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/index.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/index.html
new file mode 100644
index 0000000..ace320f
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@PWelchExperimental</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PWelchExperimental">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PWelchExperimental">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@PWelchExperimental</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PWelchExperimental.html">PWelchExperimental</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html
new file mode 100644
index 0000000..48d8c20
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html
@@ -0,0 +1,147 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PYAR</title>
+  <meta name="keywords" content="PYAR">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PYAR</a> &gt; PYAR.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PYAR
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PYAR.html" class="code" title="">PYAR</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PYAR.html" class="code" title="">PYAR</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function mAR = PYAR(trials, seconds, channel,m_ord, nfft)</a></li><li><a href="#_sub2" class="code">function extract(mAR)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(mAR)</a></li><li><a href="#_sub4" class="code">function time = getTime(mAR)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PYAR.m">PYAR.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="PYAR.html" class="code" title="">PYAR</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     
+0003     properties (Access = public)
+0004         channel;
+0005         seconds;
+0006         order;
+0007         nfft;
+0008         avgTime;
+0009     <span class="keyword">end</span>
+0010     
+0011     methods (Access = public)
+0012         <a name="_sub0" href="#_subfunctions" class="code">function mAR = PYAR(trials, seconds, channel,m_ord, nfft)</a>
+0013             <span class="keyword">if</span> nargin == 0
+0014                 mAR.seconds = 0;
+0015                 mAR.channel = 1;
+0016                 mAR.order = 20;
+0017                 mAR.nfft = 512;
+0018             <span class="keyword">elseif</span> nargin == 1
+0019                 mAR.trials = trials;
+0020                 mAR.seconds = 0;
+0021                 mAR.channel = 1;
+0022                 mAR.order = 20;
+0023                 mAR.nfft = 512;
+0024             <span class="keyword">elseif</span> nargin == 2
+0025                 mAR.trials = trials;
+0026                 mAR.channel = 1;
+0027                 mAR.seconds = seconds;
+0028                 mAR.order = 20;
+0029                 mAR.nfft = 512;
+0030             <span class="keyword">elseif</span> nargin == 3
+0031                 mAR.trials = trials;
+0032                 mAR.channel = channel;
+0033                 mAR.seconds = seconds;
+0034                 mAR.order=20;
+0035                 mAR.nfft = 512;
+0036             <span class="keyword">elseif</span> nargin == 4
+0037                 mAR.trials = trials;
+0038                 mAR.channel = channel;
+0039                 mAR.seconds = seconds;
+0040                 mAR.order = m_ord;
+0041                 mAR.nfft = 512;
+0042             <span class="keyword">elseif</span> nargin == 5
+0043                 mAR.trials = trials;
+0044                 mAR.channel = channel;
+0045                 mAR.seconds = seconds;
+0046                 mAR.order = m_ord;
+0047                 mAR.nfft = nfft;
+0048             <span class="keyword">else</span>
+0049                 error(<span class="string">'invalid number of arguments'</span>);
+0050             <span class="keyword">end</span>
+0051         <span class="keyword">end</span>
+0052         
+0053         <a name="_sub1" href="#_subfunctions" class="code">function extract(mAR)</a>
+0054             NUM_FEATURES = mAR.nfft/2+1;
+0055             numTrials = length(mAR.trials);
+0056             instances = zeros(numTrials, NUM_FEATURES);
+0057             labels = zeros(numTrials,1);
+0058             tic
+0059             <span class="keyword">for</span> i=1:numTrials
+0060                 <span class="keyword">if</span> length(mAR.seconds) ==1
+0061                 numsamples = mAR.trials{i}.samplingRate * mAR.seconds;
+0062                 <span class="keyword">if</span>(numsamples == 0)
+0063                     y = mAR.trials{i}.signal(mAR.channel,:);
+0064                 <span class="keyword">else</span>
+0065                     y = mAR.trials{i}.signal(mAR.channel, 1:numsamples);
+0066                 <span class="keyword">end</span>
+0067                 <span class="keyword">elseif</span> length(mAR.seconds) ==2
+0068                     sampleA = mAR.trials{i}.samplingRate*mAR.seconds(1) + 1;
+0069                     sampleB = mAR.trials{i}.samplingRate*mAR.seconds(2);
+0070                 <span class="keyword">else</span>
+0071                     error(<span class="string">'invalid seconds parameter'</span>);
+0072                 <span class="keyword">end</span>
+0073                 <span class="keyword">if</span> isa(mAR.filter,<span class="string">'dfilt.df2sos'</span>) || isa(mAR.filter,<span class="string">'dfilt.df2'</span>)
+0074                     y = filter(mAR.filter,y);
+0075                 <span class="keyword">elseif</span> isa(mAR.filter,<span class="string">'dfilt.dffir'</span>)
+0076                     y = filtfilt(mAR.filter.Numerator,1,y);
+0077                 <span class="keyword">end</span>
+0078                 [pyy pff] = pyulear(y,mAR.order,mAR.nfft,mAR.trials{i}.samplingRate);
+0079                 instances(i,:) = pyy;
+0080                 labels(i,1) = floor(mAR.trials{i}.label);
+0081             <span class="keyword">end</span>
+0082             mAR.avgTime = toc/numTrials;
+0083             mAR.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+0084         <span class="keyword">end</span>
+0085         
+0086         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(mAR)</a>
+0087             configInfo = sprintf(<span class="string">'PYAR\tchannel:%d\tseconds:%d\tnfft:%d\torder:%d'</span>,mAR.channel,mAR.seconds,mAR.nfft,mAR.order);
+0088         <span class="keyword">end</span>
+0089         
+0090                         
+0091         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(mAR)</a>
+0092             time = mAR.avgTime;
+0093         <span class="keyword">end</span>
+0094     <span class="keyword">end</span>
+0095    
+0096 <span class="keyword">end</span>
+0097</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.m b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.m
new file mode 100644
index 0000000..9148f94
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.m
@@ -0,0 +1,97 @@
+classdef PYAR < eegtoolkit.featextraction.FeatureExtractionBase
+    
+    properties (Access = public)
+        channel;
+        seconds;
+        order;
+        nfft;
+        avgTime;
+    end
+    
+    methods (Access = public)
+        function mAR = PYAR(trials, seconds, channel,m_ord, nfft)
+            if nargin == 0
+                mAR.seconds = 0;
+                mAR.channel = 1;
+                mAR.order = 20;
+                mAR.nfft = 512;
+            elseif nargin == 1
+                mAR.trials = trials;
+                mAR.seconds = 0;
+                mAR.channel = 1;
+                mAR.order = 20;
+                mAR.nfft = 512;
+            elseif nargin == 2
+                mAR.trials = trials;
+                mAR.channel = 1;
+                mAR.seconds = seconds;
+                mAR.order = 20;
+                mAR.nfft = 512;
+            elseif nargin == 3
+                mAR.trials = trials;
+                mAR.channel = channel;
+                mAR.seconds = seconds;
+                mAR.order=20;
+                mAR.nfft = 512;
+            elseif nargin == 4
+                mAR.trials = trials;
+                mAR.channel = channel;
+                mAR.seconds = seconds;
+                mAR.order = m_ord;
+                mAR.nfft = 512;
+            elseif nargin == 5
+                mAR.trials = trials;
+                mAR.channel = channel;
+                mAR.seconds = seconds;
+                mAR.order = m_ord;
+                mAR.nfft = nfft;
+            else
+                error('invalid number of arguments');
+            end
+        end
+        
+        function extract(mAR)
+            NUM_FEATURES = mAR.nfft/2+1;
+            numTrials = length(mAR.trials);
+            instances = zeros(numTrials, NUM_FEATURES);
+            labels = zeros(numTrials,1);
+            tic
+            for i=1:numTrials
+                if length(mAR.seconds) ==1
+                numsamples = mAR.trials{i}.samplingRate * mAR.seconds;
+                if(numsamples == 0)
+                    y = mAR.trials{i}.signal(mAR.channel,:);
+                else
+                    y = mAR.trials{i}.signal(mAR.channel, 1:numsamples);
+                end
+                elseif length(mAR.seconds) ==2
+                    sampleA = mAR.trials{i}.samplingRate*mAR.seconds(1) + 1;
+                    sampleB = mAR.trials{i}.samplingRate*mAR.seconds(2);
+                else
+                    error('invalid seconds parameter');
+                end
+                if isa(mAR.filter,'dfilt.df2sos') || isa(mAR.filter,'dfilt.df2')
+                    y = filter(mAR.filter,y);
+                elseif isa(mAR.filter,'dfilt.dffir')
+                    y = filtfilt(mAR.filter.Numerator,1,y);
+                end
+                [pyy pff] = pyulear(y,mAR.order,mAR.nfft,mAR.trials{i}.samplingRate);
+                instances(i,:) = pyy;
+                labels(i,1) = floor(mAR.trials{i}.label);
+            end
+            mAR.avgTime = toc/numTrials;
+            mAR.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+        
+        function configInfo = getConfigInfo(mAR)
+            configInfo = sprintf('PYAR\tchannel:%d\tseconds:%d\tnfft:%d\torder:%d',mAR.channel,mAR.seconds,mAR.nfft,mAR.order);
+        end
+        
+                        
+        function time = getTime(mAR)
+            time = mAR.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/graph.dot b/doc/+eegtoolkit/+featextraction/@PYAR/graph.dot
new file mode 100644
index 0000000..ce88b22
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PYAR -> PYAR;
+
+  PYAR [URL="PYAR.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/graph.html b/doc/+eegtoolkit/+featextraction/@PYAR/graph.html
new file mode 100644
index 0000000..205339d
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@PYAR</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@PYAR">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PYAR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PYAR</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PYAR" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PYAR.html" title="PYAR" alt="" coords="97,29,94,22,88,15,78,10,65,7,51,5,36,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,36,52,51,53,65,52,78,49,88,43,94,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/graph.map b/doc/+eegtoolkit/+featextraction/@PYAR/graph.map
new file mode 100644
index 0000000..9efd3ae
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="PYAR.html" title="PYAR" alt="" coords="97,29,94,22,88,15,78,10,65,7,51,5,36,7,24,10,14,15,7,22,5,29,7,37,14,43,24,49,36,52,51,53,65,52,78,49,88,43,94,37">
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/graph.png b/doc/+eegtoolkit/+featextraction/@PYAR/graph.png
new file mode 100644
index 0000000000000000000000000000000000000000..51303b40520953de077c29069db0837677377d4e
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diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/index.html b/doc/+eegtoolkit/+featextraction/@PYAR/index.html
new file mode 100644
index 0000000..b95fd23
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@PYAR</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PYAR">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PYAR">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@PYAR</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PYAR.html">PYAR</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html
new file mode 100644
index 0000000..873d3ac
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html
@@ -0,0 +1,77 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of RawSignal</title>
+  <meta name="keywords" content="RawSignal">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@RawSignal</a> &gt; RawSignal.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>RawSignal
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="RawSignal.html" class="code" title="">RawSignal</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="RawSignal.html" class="code" title="">RawSignal</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function RS = RawSignal()</a></li><li><a href="#_sub2" class="code">function RS = extract(RS)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(RS)</a></li><li><a href="#_sub4" class="code">function time = getTime(RS)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="RawSignal.m">RawSignal.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="RawSignal.html" class="code" title="">RawSignal</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     <span class="comment">%RAWSIGNAL Summary of this class goes here</span>
+0003     <span class="comment">%   Detailed explanation goes here</span>
+0004     
+0005     properties (Access = public)
+0006     <span class="keyword">end</span>
+0007     
+0008     methods (Access = public)
+0009         <a name="_sub0" href="#_subfunctions" class="code">function RS = RawSignal()</a>
+0010 <span class="comment">%             RS.instanceSet = eegtoolkit.util.RawSignalSet(RS.trials);</span>
+0011         <span class="keyword">end</span>
+0012         
+0013         <a name="_sub1" href="#_subfunctions" class="code">function RS = extract(RS)</a>
+0014             RS.instanceSet = eegtoolkit.util.RawSignalSet(RS.trials);
+0015         <span class="keyword">end</span>
+0016         
+0017         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(RS)</a>
+0018             configInfo = <span class="string">'\n'</span>;
+0019         <span class="keyword">end</span>
+0020         
+0021         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(RS)</a>
+0022             time = 0;
+0023         <span class="keyword">end</span>
+0024     <span class="keyword">end</span>
+0025     
+0026 <span class="keyword">end</span>
+0027</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.m b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.m
new file mode 100644
index 0000000..c08003a
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.m
@@ -0,0 +1,27 @@
+classdef RawSignal < eegtoolkit.featextraction.FeatureExtractionBase
+    %RAWSIGNAL Summary of this class goes here
+    %   Detailed explanation goes here
+    
+    properties (Access = public)
+    end
+    
+    methods (Access = public)
+        function RS = RawSignal()
+%             RS.instanceSet = eegtoolkit.util.RawSignalSet(RS.trials);
+        end
+        
+        function RS = extract(RS)
+            RS.instanceSet = eegtoolkit.util.RawSignalSet(RS.trials);
+        end
+        
+        function configInfo = getConfigInfo(RS)
+            configInfo = '\n';
+        end
+        
+        function time = getTime(RS)
+            time = 0;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.dot b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.dot
new file mode 100644
index 0000000..effc195
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  RawSignal -> RawSignal;
+
+  RawSignal [URL="RawSignal.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html
new file mode 100644
index 0000000..14a5ac5
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@RawSignal</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@RawSignal">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@RawSignal">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@RawSignal</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@RawSignal" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="RawSignal.html" title="RawSignal" alt="" coords="137,29,133,22,124,15,109,10,91,7,71,5,50,7,32,10,17,15,8,22,5,29,8,37,17,43,32,49,50,52,71,53,91,52,109,49,124,43,133,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.map b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.map
new file mode 100644
index 0000000..9455564
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="RawSignal.html" title="RawSignal" alt="" coords="137,29,133,22,124,15,109,10,91,7,71,5,50,7,32,10,17,15,8,22,5,29,8,37,17,43,32,49,50,52,71,53,91,52,109,49,124,43,133,37">
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.png b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.png
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diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/index.html b/doc/+eegtoolkit/+featextraction/@RawSignal/index.html
new file mode 100644
index 0000000..8f53713
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@RawSignal</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@RawSignal">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@RawSignal">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@RawSignal</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="RawSignal.html">RawSignal</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/STFT.html b/doc/+eegtoolkit/+featextraction/@STFT/STFT.html
new file mode 100644
index 0000000..83bc874
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/STFT.html
@@ -0,0 +1,151 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of STFT</title>
+  <meta name="keywords" content="STFT">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@STFT</a> &gt; STFT.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>STFT
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="STFT.html" class="code" title="">STFT</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="STFT.html" class="code" title="">STFT</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function mSTFT = STFT(trials, seconds, channel,rangeFreq)</a></li><li><a href="#_sub2" class="code">function extract(mSTFT)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(mSTFT)</a></li><li><a href="#_sub4" class="code">function time = getTime(mSTFT)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="STFT.m">STFT.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="STFT.html" class="code" title="">STFT</a> &lt; eegtoolkit.featextraction.FeatureExtractionBase
+0002     
+0003     properties (Access = public)
+0004         channel;
+0005         seconds;
+0006         Frange;
+0007         avgTime;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods (Access = public)   
+0011         <a name="_sub0" href="#_subfunctions" class="code">function mSTFT = STFT(trials, seconds, channel,rangeFreq)</a>
+0012             <span class="keyword">if</span> nargin == 0
+0013                 mSTFT.seconds = 0;
+0014                 mSTFT.channel = 1;
+0015                 mSTFT.Frange(1) = 0;
+0016 <span class="comment">%                 mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;</span>
+0017             <span class="keyword">elseif</span> nargin == 1
+0018                 mSTFT.trials = trials;
+0019                 mSTFT.seconds = 0;
+0020                 mSTFT.channel = 1;
+0021                 mSTFT.Frange(1) = 0;
+0022                 mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+0023             <span class="keyword">elseif</span> nargin == 2
+0024                 mSTFT.trials = trials;
+0025                 mSTFT.channel = 1;
+0026                 mSTFT.seconds = seconds;
+0027                 mSTFT.Frange(1) = 0;
+0028                 mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+0029             <span class="keyword">elseif</span> nargin == 3
+0030                 mSTFT.trials = trials;
+0031                 mSTFT.channel = channel;
+0032                 mSTFT.seconds = seconds;
+0033                 mSTFT.Frange(1) = 0;
+0034                 mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+0035             <span class="keyword">elseif</span> nargin==4
+0036                 
+0037                 mSTFT.trials = trials;
+0038                 
+0039                 <span class="keyword">if</span> prod(size(rangeFreq)) ~=2
+0040                     error(<span class="string">'vector for frequency range must has two elements'</span>)
+0041                 <span class="keyword">end</span>
+0042                 <span class="keyword">if</span> rangeFreq(1)&gt;=rangeFreq(2)
+0043                     error(<span class="string">'first element must be smaller.'</span>);
+0044                 <span class="keyword">end</span>
+0045                 <span class="keyword">if</span> (rangeFreq(1)&lt;0 || rangeFreq(2)&gt;mSTFT.trials{1}.samplingRate)
+0046                     error(<span class="string">'invalid values for frequency range'</span>);
+0047                 <span class="keyword">end</span>
+0048                 
+0049                 mSTFT.channel = channel;
+0050                 mSTFT.seconds = seconds;
+0051                 mSTFT.Frange(1) = rangeFreq(1);
+0052                 mSTFT.Frange(2) = rangeFreq(2);
+0053             <span class="keyword">else</span>
+0054                 error(<span class="string">'invalid number of arguments'</span>);
+0055             <span class="keyword">end</span>
+0056         <span class="keyword">end</span>
+0057         
+0058         <a name="_sub1" href="#_subfunctions" class="code">function extract(mSTFT)</a>
+0059             mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+0060             numsamples = mSTFT.trials{1}.samplingRate * mSTFT.seconds;
+0061             <span class="keyword">if</span> (numsamples == 0)                    
+0062                 numsamples = size(mSTFT.trials{1}.signal(mSTFT.channel,:),2);                             
+0063             <span class="keyword">end</span>
+0064             tic
+0065             numTrials = length(mSTFT.trials);
+0066             y = mSTFT.trials{1}.signal(mSTFT.channel, 1:numsamples);
+0067             [S,F,T,P]=spectrogram(y,[],[],[mSTFT.Frange(1):0.5:mSTFT.Frange(2)],mSTFT.trials{1}.samplingRate);
+0068             instances = zeros(numTrials, length(P(:)));
+0069             labels = zeros(numTrials,1);
+0070             <span class="keyword">for</span> i=1:numTrials
+0071                 numsamples = mSTFT.trials{i}.samplingRate * mSTFT.seconds;
+0072                 <span class="keyword">if</span>(numsamples == 0)
+0073                     y = mSTFT.trials{i}.signal(mSTFT.channel,:);
+0074                 <span class="keyword">else</span>
+0075                     y = mSTFT.trials{i}.signal(mSTFT.channel, 1:numsamples);
+0076                 <span class="keyword">end</span>                
+0077                 
+0078                 [S,F,T,P]=spectrogram(y,[],[],[mSTFT.Frange(1):0.5:mSTFT.Frange(2)],mSTFT.trials{i}.samplingRate);
+0079                 instances(i,:) = P(:);
+0080                 labels(i,1) = floor(mSTFT.trials{i}.label);
+0081             <span class="keyword">end</span>
+0082             mSTFT.avgTime = toc/numTrials;
+0083             mSTFT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+0084         <span class="keyword">end</span>
+0085         
+0086         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(mSTFT)</a>
+0087             <span class="keyword">if</span> length(mSTFT.Frange) == 2
+0088                 configInfo = sprintf(<span class="string">'STFT\tchannel:%d\tseconds:%d\tfrange1:%d\tfrange2:%d'</span>,mSTFT.channel,mSTFT.seconds,mSTFT.Frange(1),mSTFT.Frange(2));
+0089             <span class="keyword">else</span>
+0090                 configInfo = sprintf(<span class="string">'STFT\tchannel:%d\tseconds:%d\tfrange1:%d\tfrange2:unset'</span>,mSTFT.channel,mSTFT.seconds,mSTFT.Frange(1));
+0091             <span class="keyword">end</span>
+0092         <span class="keyword">end</span>
+0093         
+0094                         
+0095         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(mSTFT)</a>
+0096             time = mSTFT.avgTime;
+0097         <span class="keyword">end</span>
+0098     <span class="keyword">end</span>
+0099    
+0100 <span class="keyword">end</span>
+0101</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/STFT.m b/doc/+eegtoolkit/+featextraction/@STFT/STFT.m
new file mode 100644
index 0000000..e7bde00
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/STFT.m
@@ -0,0 +1,101 @@
+classdef STFT < eegtoolkit.featextraction.FeatureExtractionBase
+    
+    properties (Access = public)
+        channel;
+        seconds;
+        Frange;
+        avgTime;
+    end
+    
+    methods (Access = public)   
+        function mSTFT = STFT(trials, seconds, channel,rangeFreq)
+            if nargin == 0
+                mSTFT.seconds = 0;
+                mSTFT.channel = 1;
+                mSTFT.Frange(1) = 0;
+%                 mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+            elseif nargin == 1
+                mSTFT.trials = trials;
+                mSTFT.seconds = 0;
+                mSTFT.channel = 1;
+                mSTFT.Frange(1) = 0;
+                mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+            elseif nargin == 2
+                mSTFT.trials = trials;
+                mSTFT.channel = 1;
+                mSTFT.seconds = seconds;
+                mSTFT.Frange(1) = 0;
+                mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+            elseif nargin == 3
+                mSTFT.trials = trials;
+                mSTFT.channel = channel;
+                mSTFT.seconds = seconds;
+                mSTFT.Frange(1) = 0;
+                mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+            elseif nargin==4
+                
+                mSTFT.trials = trials;
+                
+                if prod(size(rangeFreq)) ~=2
+                    error('vector for frequency range must has two elements')
+                end
+                if rangeFreq(1)>=rangeFreq(2)
+                    error('first element must be smaller.');
+                end
+                if (rangeFreq(1)<0 || rangeFreq(2)>mSTFT.trials{1}.samplingRate)
+                    error('invalid values for frequency range');
+                end
+                
+                mSTFT.channel = channel;
+                mSTFT.seconds = seconds;
+                mSTFT.Frange(1) = rangeFreq(1);
+                mSTFT.Frange(2) = rangeFreq(2);
+            else
+                error('invalid number of arguments');
+            end
+        end
+        
+        function extract(mSTFT)
+            mSTFT.Frange(2) = mSTFT.trials{1}.samplingRate;
+            numsamples = mSTFT.trials{1}.samplingRate * mSTFT.seconds;
+            if (numsamples == 0)                    
+                numsamples = size(mSTFT.trials{1}.signal(mSTFT.channel,:),2);                             
+            end
+            tic
+            numTrials = length(mSTFT.trials);
+            y = mSTFT.trials{1}.signal(mSTFT.channel, 1:numsamples);
+            [S,F,T,P]=spectrogram(y,[],[],[mSTFT.Frange(1):0.5:mSTFT.Frange(2)],mSTFT.trials{1}.samplingRate);
+            instances = zeros(numTrials, length(P(:)));
+            labels = zeros(numTrials,1);
+            for i=1:numTrials
+                numsamples = mSTFT.trials{i}.samplingRate * mSTFT.seconds;
+                if(numsamples == 0)
+                    y = mSTFT.trials{i}.signal(mSTFT.channel,:);
+                else
+                    y = mSTFT.trials{i}.signal(mSTFT.channel, 1:numsamples);
+                end                
+                
+                [S,F,T,P]=spectrogram(y,[],[],[mSTFT.Frange(1):0.5:mSTFT.Frange(2)],mSTFT.trials{i}.samplingRate);
+                instances(i,:) = P(:);
+                labels(i,1) = floor(mSTFT.trials{i}.label);
+            end
+            mSTFT.avgTime = toc/numTrials;
+            mSTFT.instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+        end
+        
+        function configInfo = getConfigInfo(mSTFT)
+            if length(mSTFT.Frange) == 2
+                configInfo = sprintf('STFT\tchannel:%d\tseconds:%d\tfrange1:%d\tfrange2:%d',mSTFT.channel,mSTFT.seconds,mSTFT.Frange(1),mSTFT.Frange(2));
+            else
+                configInfo = sprintf('STFT\tchannel:%d\tseconds:%d\tfrange1:%d\tfrange2:unset',mSTFT.channel,mSTFT.seconds,mSTFT.Frange(1));
+            end
+        end
+        
+                        
+        function time = getTime(mSTFT)
+            time = mSTFT.avgTime;
+        end
+    end
+   
+end
+
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/graph.dot b/doc/+eegtoolkit/+featextraction/@STFT/graph.dot
new file mode 100644
index 0000000..b300e03
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  STFT -> STFT;
+
+  STFT [URL="STFT.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/graph.html b/doc/+eegtoolkit/+featextraction/@STFT/graph.html
new file mode 100644
index 0000000..97c3e7e
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@STFT</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@STFT">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@STFT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@STFT</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@STFT" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="STFT.html" title="STFT" alt="" coords="88,29,86,22,80,15,71,10,60,7,47,5,34,7,22,10,13,15,7,22,5,29,7,37,13,43,22,49,34,52,47,53,60,52,71,49,80,43,86,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/graph.map b/doc/+eegtoolkit/+featextraction/@STFT/graph.map
new file mode 100644
index 0000000..1a17266
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="STFT.html" title="STFT" alt="" coords="88,29,86,22,80,15,71,10,60,7,47,5,34,7,22,10,13,15,7,22,5,29,7,37,13,43,22,49,34,52,47,53,60,52,71,49,80,43,86,37">
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/graph.png b/doc/+eegtoolkit/+featextraction/@STFT/graph.png
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diff --git a/doc/+eegtoolkit/+featextraction/@STFT/index.html b/doc/+eegtoolkit/+featextraction/@STFT/index.html
new file mode 100644
index 0000000..46bed9b
--- /dev/null
+++ b/doc/+eegtoolkit/+featextraction/@STFT/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featextraction/@STFT</title>
+  <meta name="keywords" content="./+eegtoolkit/+featextraction/@STFT">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@STFT">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featextraction/@STFT</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="STFT.html">STFT</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/FEAST.html b/doc/+eegtoolkit/+featselection/@FEAST/FEAST.html
new file mode 100644
index 0000000..8f4c41f
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/FEAST.html
@@ -0,0 +1,126 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FEAST</title>
+  <meta name="keywords" content="FEAST">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@FEAST</a> &gt; FEAST.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FEAST
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FEAST.html" class="code" title="">FEAST</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FEAST.html" class="code" title="">FEAST</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function FF = FEAST(instanceSet,algorithm, numtoSelect, param1, param2)</a></li><li><a href="#_sub2" class="code">function FF = compute(FF)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(FF)</a></li><li><a href="#_sub4" class="code">function time = getTime(FF)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FEAST.m">FEAST.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="FEAST.html" class="code" title="">FEAST</a> &lt; eegtoolkit.featselection.FeatureSelectionBase
+0002     properties (Constant)
+0003         ALGORITHM_MIM = <span class="string">'mim'</span>;
+0004         ALGORITHM_MRMR = <span class="string">'mrmr'</span>;
+0005         ALGORITHM_CMIM = <span class="string">'cmim'</span>;
+0006         ALGORITHM_JMI = <span class="string">'jmi'</span>;
+0007         ALGORITHM_DISR = <span class="string">'disr'</span>;
+0008         ALGORITHM_CIFE = <span class="string">'cife'</span>;
+0009         ALGORITHM_ICAP = <span class="string">'icap'</span>;
+0010         ALGORITHM_CONDRED = <span class="string">'condred'</span>;
+0011         ALGORITHM_CMI = <span class="string">'cmi'</span>;
+0012         ALGORITHM_RELIEF = <span class="string">'relief'</span>;
+0013         ALGORITHM_MIFS = <span class="string">'mifs'</span> <span class="comment">%beta parameter required</span>
+0014         ALGORITHM_BETAGAMMA = <span class="string">'betagamma'</span>; <span class="comment">%beta and gamma parameters required</span>
+0015         ALGORITHM_FCBF = <span class="string">'fcbf'</span>; <span class="comment">%threshold parameter required</span>
+0016     <span class="keyword">end</span>
+0017     properties (Access = public)
+0018         algorithm;
+0019         numToSelect;
+0020         parameter1;
+0021         parameter2;
+0022         avgTime;
+0023     <span class="keyword">end</span>
+0024     
+0025     methods
+0026         <a name="_sub0" href="#_subfunctions" class="code">function FF = FEAST(instanceSet,algorithm, numtoSelect, param1, param2)</a>
+0027             <span class="keyword">if</span> nargin == 0
+0028                 FF.algorithm = <span class="string">'icap'</span>;
+0029                 FF.numToSelect = 85;
+0030             <span class="keyword">end</span>
+0031             <span class="keyword">if</span> nargin &gt; 1
+0032                 FF.originalInstanceSet = instanceSet;
+0033                 FF.algorithm = algorithm;
+0034             <span class="keyword">end</span>
+0035             <span class="keyword">if</span> nargin &gt; 2
+0036                 FF.numToSelect = numtoSelect;
+0037             <span class="keyword">end</span>
+0038             <span class="keyword">if</span> nargin &gt; 3
+0039                 FF.parameter1 = param1;
+0040             <span class="keyword">end</span>
+0041             <span class="keyword">if</span> nargin &gt; 4
+0042                 FF.parameter2 = param2;
+0043             <span class="keyword">end</span>
+0044         <span class="keyword">end</span>
+0045         
+0046         <a name="_sub1" href="#_subfunctions" class="code">function FF = compute(FF)</a>
+0047             tic
+0048             <span class="keyword">if</span> (strcmp(FF.algorithm,FF.ALGORITHM_MIFS) == 1) || (strcmp(FF.algorithm, FF.ALGORITHM_FCBF) == 1)
+0049                 indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels, FF.parameter1);
+0050             <span class="keyword">elseif</span> strcmp(FF.algorithm, FF.ALGORITHM_BETAGAMMA) == 1
+0051                 indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels, FF.parameter1, FF.parameter2);
+0052             <span class="keyword">else</span>
+0053                 indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels);
+0054             <span class="keyword">end</span>
+0055             dataset = FF.originalInstanceSet.getInstances;
+0056             [inst, ~] = size(dataset);
+0057             FF.avgTime = toc/inst;
+0058             FF.filteredInstanceSet = eegtoolkit.util.InstanceSet([dataset(:,indices) FF.originalInstanceSet.getLabels]);
+0059         <span class="keyword">end</span>
+0060         
+0061         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(FF)</a>
+0062             <span class="keyword">if</span> (strcmp(FF.algorithm,FF.ALGORITHM_MIFS) == 1) || (strcmp(FF.algorithm, FF.ALGORITHM_FCBF) == 1)
+0063                 configInfo = sprintf(<span class="string">'FEAST\talgorithm:%s\tnumtoselect:%d\tparam1:%d'</span>,FF.algorithm, FF.numToSelect, FF.parameter1);
+0064             <span class="keyword">elseif</span> strcmp(FF.algorithm, FF.ALGORITHM_BETAGAMMA) == 1
+0065                 configInfo = sprintf(<span class="string">'FEAST\talgorithm:%s\tnumtoselect:%d\tparam1:%d\tparam2:%d'</span>,FF.algorithm, FF.numToSelect, FF.parameter1, FF.parameter2);
+0066             <span class="keyword">else</span>
+0067                 configInfo = sprintf(<span class="string">'FEAST\talgorithm:%s\tnumtoselect:%d'</span>,FF.algorithm, FF.numToSelect);
+0068             <span class="keyword">end</span>
+0069         <span class="keyword">end</span>
+0070         
+0071         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(FF)</a>
+0072             time = FF.avgTime;
+0073         <span class="keyword">end</span>
+0074     <span class="keyword">end</span>
+0075     
+0076 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/FEAST.m b/doc/+eegtoolkit/+featselection/@FEAST/FEAST.m
new file mode 100644
index 0000000..bdfeb64
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/FEAST.m
@@ -0,0 +1,76 @@
+classdef FEAST < eegtoolkit.featselection.FeatureSelectionBase
+    properties (Constant)
+        ALGORITHM_MIM = 'mim';
+        ALGORITHM_MRMR = 'mrmr';
+        ALGORITHM_CMIM = 'cmim';
+        ALGORITHM_JMI = 'jmi';
+        ALGORITHM_DISR = 'disr';
+        ALGORITHM_CIFE = 'cife';
+        ALGORITHM_ICAP = 'icap';
+        ALGORITHM_CONDRED = 'condred';
+        ALGORITHM_CMI = 'cmi';
+        ALGORITHM_RELIEF = 'relief';
+        ALGORITHM_MIFS = 'mifs' %beta parameter required
+        ALGORITHM_BETAGAMMA = 'betagamma'; %beta and gamma parameters required
+        ALGORITHM_FCBF = 'fcbf'; %threshold parameter required
+    end
+    properties (Access = public)
+        algorithm;
+        numToSelect;
+        parameter1;
+        parameter2;
+        avgTime;
+    end
+    
+    methods
+        function FF = FEAST(instanceSet,algorithm, numtoSelect, param1, param2)
+            if nargin == 0
+                FF.algorithm = 'icap';
+                FF.numToSelect = 85;
+            end
+            if nargin > 1
+                FF.originalInstanceSet = instanceSet;
+                FF.algorithm = algorithm;
+            end
+            if nargin > 2
+                FF.numToSelect = numtoSelect;
+            end
+            if nargin > 3
+                FF.parameter1 = param1;
+            end
+            if nargin > 4
+                FF.parameter2 = param2;
+            end
+        end
+        
+        function FF = compute(FF)
+            tic
+            if (strcmp(FF.algorithm,FF.ALGORITHM_MIFS) == 1) || (strcmp(FF.algorithm, FF.ALGORITHM_FCBF) == 1)
+                indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels, FF.parameter1);
+            elseif strcmp(FF.algorithm, FF.ALGORITHM_BETAGAMMA) == 1
+                indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels, FF.parameter1, FF.parameter2);
+            else
+                indices = feast(FF.algorithm, FF.numToSelect, FF.originalInstanceSet.getInstances, FF.originalInstanceSet.getLabels);
+            end
+            dataset = FF.originalInstanceSet.getInstances;
+            [inst, ~] = size(dataset);
+            FF.avgTime = toc/inst;
+            FF.filteredInstanceSet = eegtoolkit.util.InstanceSet([dataset(:,indices) FF.originalInstanceSet.getLabels]);
+        end
+        
+        function configInfo = getConfigInfo(FF)
+            if (strcmp(FF.algorithm,FF.ALGORITHM_MIFS) == 1) || (strcmp(FF.algorithm, FF.ALGORITHM_FCBF) == 1)
+                configInfo = sprintf('FEAST\talgorithm:%s\tnumtoselect:%d\tparam1:%d',FF.algorithm, FF.numToSelect, FF.parameter1);
+            elseif strcmp(FF.algorithm, FF.ALGORITHM_BETAGAMMA) == 1
+                configInfo = sprintf('FEAST\talgorithm:%s\tnumtoselect:%d\tparam1:%d\tparam2:%d',FF.algorithm, FF.numToSelect, FF.parameter1, FF.parameter2);
+            else
+                configInfo = sprintf('FEAST\talgorithm:%s\tnumtoselect:%d',FF.algorithm, FF.numToSelect);
+            end
+        end
+        
+        function time = getTime(FF)
+            time = FF.avgTime;
+        end
+    end
+    
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/graph.dot b/doc/+eegtoolkit/+featselection/@FEAST/graph.dot
new file mode 100644
index 0000000..a790ffe
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FEAST -> FEAST;
+
+  FEAST [URL="FEAST.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/graph.html b/doc/+eegtoolkit/+featselection/@FEAST/graph.html
new file mode 100644
index 0000000..079ad91
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featselection/@FEAST</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@FEAST">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@FEAST">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featselection/@FEAST</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@FEAST" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FEAST.html" title="FEAST" alt="" coords="105,29,102,22,95,15,84,10,70,7,55,5,39,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,39,52,55,53,70,52,84,49,95,43,102,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/graph.map b/doc/+eegtoolkit/+featselection/@FEAST/graph.map
new file mode 100644
index 0000000..9bbd9b1
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="FEAST.html" title="FEAST" alt="" coords="105,29,102,22,95,15,84,10,70,7,55,5,39,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,39,52,55,53,70,52,84,49,95,43,102,37">
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/graph.png b/doc/+eegtoolkit/+featselection/@FEAST/graph.png
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diff --git a/doc/+eegtoolkit/+featselection/@FEAST/index.html b/doc/+eegtoolkit/+featselection/@FEAST/index.html
new file mode 100644
index 0000000..67b79c7
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FEAST/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featselection/@FEAST</title>
+  <meta name="keywords" content="./+eegtoolkit/+featselection/@FEAST">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@FEAST">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featselection/@FEAST</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FEAST.html">FEAST</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.html
new file mode 100644
index 0000000..b7b4bf9
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.html
@@ -0,0 +1,93 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FeatureSelectionBase</title>
+  <meta name="keywords" content="FeatureSelectionBase">
+  <meta name="description" content="Abstract class for feature selection. Implement the functions for any">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@FeatureSelectionBase</a> &gt; FeatureSelectionBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FeatureSelectionBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>Abstract class for feature selection. Implement the functions for any</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Abstract class for feature selection. Implement the functions for any
+ feature selection method (e.g. PCA, SVD, FEAST, etc.)
+ 
+ Properties:
+ originalInstanceSet: Input - the original instanceSet with the features
+ filteredInstanceSet: Output - the filtered instanceSet
+ 
+ Functions:
+Implement this function to process the originalInstanceSet trials and 
+return the filteredInstanceSet
+   obj.compute();
+Info &amp; run time so that the experiments are easily documented. configInfo
+is a string with the configuration information and time is of type double.
+   configInfo = obj.getConfigInfo();
+   time = obj.getTime();</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FeatureSelectionBase.html" class="code" title="">FeatureSelectionBase</a>	Abstract class for feature selection. Implement the functions for any</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FeatureSelectionBase.html" class="code" title="">FeatureSelectionBase</a>	Abstract class for feature selection. Implement the functions for any</li></ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FeatureSelectionBase.m">FeatureSelectionBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Abstract class for feature selection. Implement the functions for any</span>
+0002 <span class="comment">% feature selection method (e.g. PCA, SVD, FEAST, etc.)</span>
+0003 <span class="comment">%</span>
+0004 <span class="comment">% Properties:</span>
+0005 <span class="comment">% originalInstanceSet: Input - the original instanceSet with the features</span>
+0006 <span class="comment">% filteredInstanceSet: Output - the filtered instanceSet</span>
+0007 <span class="comment">%</span>
+0008 <span class="comment">% Functions:</span>
+0009 <span class="comment">%Implement this function to process the originalInstanceSet trials and</span>
+0010 <span class="comment">%return the filteredInstanceSet</span>
+0011 <span class="comment">%   obj.compute();</span>
+0012 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0013 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0014 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0015 <span class="comment">%   time = obj.getTime();</span>
+0016 
+0017 classdef (Abstract) <a href="FeatureSelectionBase.html" class="code" title="">FeatureSelectionBase</a> &lt; handle
+0018     
+0019     properties
+0020         originalInstanceSet; <span class="comment">% Input: The original dataset</span>
+0021         filteredInstanceSet; <span class="comment">% Output: The filtered dataset</span>
+0022     <span class="keyword">end</span>
+0023     
+0024     methods (Abstract = true)
+0025         obj = compute(obj);
+0026         configInfo = getConfigInfo(obj);
+0027         time = getTime(obj);
+0028     <span class="keyword">end</span>
+0029     
+0030 <span class="keyword">end</span>
+0031</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m
new file mode 100644
index 0000000..7101cc1
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.m
@@ -0,0 +1,31 @@
+% Abstract class for feature selection. Implement the functions for any
+% feature selection method (e.g. PCA, SVD, FEAST, etc.)
+% 
+% Properties:
+% originalInstanceSet: Input - the original instanceSet with the features
+% filteredInstanceSet: Output - the filtered instanceSet
+% 
+% Functions:
+%Implement this function to process the originalInstanceSet trials and 
+%return the filteredInstanceSet
+%   obj.compute();
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+classdef (Abstract) FeatureSelectionBase < handle
+    
+    properties
+        originalInstanceSet; % Input: The original dataset
+        filteredInstanceSet; % Output: The filtered dataset
+    end
+    
+    methods (Abstract = true)
+        obj = compute(obj);
+        configInfo = getConfigInfo(obj);
+        time = getTime(obj);
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.dot b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.dot
new file mode 100644
index 0000000..9de1c9a
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FeatureSelectionBase -> FeatureSelectionBase;
+
+  FeatureSelectionBase [URL="FeatureSelectionBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.html
new file mode 100644
index 0000000..4ea287e
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featselection/@FeatureSelectionBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@FeatureSelectionBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@FeatureSelectionBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featselection/@FeatureSelectionBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@FeatureSelectionBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FeatureSelectionBase.html" title="FeatureSelectionBase" alt="" coords="237,29,232,22,215,15,190,10,157,7,121,5,85,7,53,10,27,15,11,22,5,29,11,37,27,43,53,49,85,52,121,53,157,52,190,49,215,43,232,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.map b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.map
new file mode 100644
index 0000000..fa3a33d
--- /dev/null
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diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/index.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/index.html
new file mode 100644
index 0000000..cd1ebcf
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featselection/@FeatureSelectionBase</title>
+  <meta name="keywords" content="./+eegtoolkit/+featselection/@FeatureSelectionBase">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@FeatureSelectionBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FeatureSelectionBase.html">FeatureSelectionBase</a></td><td>Abstract class for feature selection. Implement the functions for any </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/PCA.html b/doc/+eegtoolkit/+featselection/@PCA/PCA.html
new file mode 100644
index 0000000..41fbbc6
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/PCA.html
@@ -0,0 +1,82 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PCA</title>
+  <meta name="keywords" content="PCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@PCA</a> &gt; PCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PCA.html" class="code" title="">PCA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PCA.html" class="code" title="">PCA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function PCA = PCA(instanceSet,componentNum)</a></li><li><a href="#_sub2" class="code">function PCA = compute(PCA)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(PCA)</a></li><li><a href="#_sub4" class="code">function time = getTime(PCA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PCA.m">PCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="PCA.html" class="code" title="">PCA</a> &lt; eegtoolkit.featselection.FeatureSelectionBase
+0002     properties (Access = public)
+0003         componentNum;
+0004         avgTime;
+0005     <span class="keyword">end</span>
+0006     methods
+0007         <a name="_sub0" href="#_subfunctions" class="code">function PCA = PCA(instanceSet,componentNum)</a>
+0008             <span class="keyword">if</span> nargin == 0
+0009                 PCA.componentNum = 50;
+0010             <span class="keyword">else</span>
+0011                 PCA.componentNum = componentNum;
+0012                 PCA.originalInstanceSet = instanceSet;
+0013             <span class="keyword">end</span>
+0014         <span class="keyword">end</span>
+0015         
+0016         <a name="_sub1" href="#_subfunctions" class="code">function PCA = compute(PCA)</a>
+0017             ins = PCA.originalInstanceSet.getInstances;
+0018             [numInst,~] = size(ins);
+0019             tic
+0020             [~,score,~,~,~] = pca(ins,<span class="string">'NumComponents'</span>,PCA.componentNum);
+0021             PCA.avgTime = toc/numInst;
+0022             PCA.filteredInstanceSet = eegtoolkit.util.InstanceSet(score,PCA.originalInstanceSet.getLabels);
+0023         <span class="keyword">end</span>
+0024         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(PCA)</a>
+0025             configInfo = sprintf(<span class="string">'PCA\tcomponents:%d'</span>, PCA.componentNum);
+0026         <span class="keyword">end</span>
+0027         
+0028         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(PCA)</a>
+0029             time = PCA.avgTime;
+0030         <span class="keyword">end</span>
+0031     <span class="keyword">end</span>
+0032 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/PCA.m b/doc/+eegtoolkit/+featselection/@PCA/PCA.m
new file mode 100644
index 0000000..d0f8d4f
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/PCA.m
@@ -0,0 +1,32 @@
+classdef PCA < eegtoolkit.featselection.FeatureSelectionBase
+    properties (Access = public)
+        componentNum;
+        avgTime;
+    end
+    methods
+        function PCA = PCA(instanceSet,componentNum)
+            if nargin == 0
+                PCA.componentNum = 50;
+            else
+                PCA.componentNum = componentNum;
+                PCA.originalInstanceSet = instanceSet;
+            end
+        end
+        
+        function PCA = compute(PCA)
+            ins = PCA.originalInstanceSet.getInstances;
+            [numInst,~] = size(ins);
+            tic
+            [~,score,~,~,~] = pca(ins,'NumComponents',PCA.componentNum);
+            PCA.avgTime = toc/numInst;
+            PCA.filteredInstanceSet = eegtoolkit.util.InstanceSet(score,PCA.originalInstanceSet.getLabels);
+        end
+        function configInfo = getConfigInfo(PCA)
+            configInfo = sprintf('PCA\tcomponents:%d', PCA.componentNum);
+        end
+        
+        function time = getTime(PCA)
+            time = PCA.avgTime;
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/graph.dot b/doc/+eegtoolkit/+featselection/@PCA/graph.dot
new file mode 100644
index 0000000..476a8be
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PCA -> PCA;
+
+  PCA [URL="PCA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/graph.html b/doc/+eegtoolkit/+featselection/@PCA/graph.html
new file mode 100644
index 0000000..905c0d7
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featselection/@PCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@PCA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@PCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featselection/@PCA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@PCA" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PCA.html" title="PCA" alt="" coords="79,29,77,22,71,15,63,10,53,7,41,5,30,7,19,10,11,15,6,22,4,29,6,37,11,43,19,49,30,52,41,53,53,52,63,49,71,43,77,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/graph.map b/doc/+eegtoolkit/+featselection/@PCA/graph.map
new file mode 100644
index 0000000..c747cc7
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="PCA.html" title="PCA" alt="" coords="79,29,77,22,71,15,63,10,53,7,41,5,30,7,19,10,11,15,6,22,4,29,6,37,11,43,19,49,30,52,41,53,53,52,63,49,71,43,77,37">
diff --git a/doc/+eegtoolkit/+featselection/@PCA/graph.png b/doc/+eegtoolkit/+featselection/@PCA/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+featselection/@PCA/index.html b/doc/+eegtoolkit/+featselection/@PCA/index.html
new file mode 100644
index 0000000..ddb326c
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@PCA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featselection/@PCA</title>
+  <meta name="keywords" content="./+eegtoolkit/+featselection/@PCA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@PCA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featselection/@PCA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PCA.html">PCA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/SVD.html b/doc/+eegtoolkit/+featselection/@SVD/SVD.html
new file mode 100644
index 0000000..61e1deb
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/SVD.html
@@ -0,0 +1,82 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of SVD</title>
+  <meta name="keywords" content="SVD">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@SVD</a> &gt; SVD.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>SVD
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SVD.html" class="code" title="">SVD</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SVD.html" class="code" title="">SVD</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function SVD = SVD(instanceSet,modes)</a></li><li><a href="#_sub2" class="code">function SVD = compute(SVD)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(SVD)</a></li><li><a href="#_sub4" class="code">function time = getTime(SVD)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="SVD.m">SVD.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="SVD.html" class="code" title="">SVD</a> &lt; eegtoolkit.featselection.FeatureSelectionBase;
+0002     properties (Access = public)
+0003         modes;
+0004         avgTime;
+0005     <span class="keyword">end</span>
+0006     methods
+0007         <a name="_sub0" href="#_subfunctions" class="code">function SVD = SVD(instanceSet,modes)</a>
+0008             <span class="keyword">if</span> nargin == 0
+0009                 SVD.modes = 80;
+0010             <span class="keyword">else</span>
+0011                 SVD.modes = modes;
+0012                 SVD.originalInstanceSet = instanceSet;
+0013             <span class="keyword">end</span>
+0014         <span class="keyword">end</span>
+0015         
+0016         <a name="_sub1" href="#_subfunctions" class="code">function SVD = compute(SVD)</a>
+0017             tic
+0018             [U, S, V] = svd(SVD.originalInstanceSet.getInstances);
+0019             data_svd = U*S(:,1:SVD.modes)*V(1:SVD.modes,1:SVD.modes)';
+0020             [numInst, ~] = size(data_svd);
+0021             SVD.avgTime = toc/numInst;
+0022             SVD.filteredInstanceSet = eegtoolkit.util.InstanceSet(data_svd, SVD.originalInstanceSet.getLabels);
+0023         <span class="keyword">end</span>
+0024         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(SVD)</a>
+0025             configInfo = sprintf(<span class="string">'SVD\tmodes:%d'</span>, SVD.modes);
+0026         <span class="keyword">end</span>
+0027         
+0028         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(SVD)</a>
+0029             time = SVD.avgTime;
+0030         <span class="keyword">end</span>
+0031     <span class="keyword">end</span>
+0032 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/SVD.m b/doc/+eegtoolkit/+featselection/@SVD/SVD.m
new file mode 100644
index 0000000..e84a121
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/SVD.m
@@ -0,0 +1,32 @@
+classdef SVD < eegtoolkit.featselection.FeatureSelectionBase;
+    properties (Access = public)
+        modes;
+        avgTime;
+    end
+    methods
+        function SVD = SVD(instanceSet,modes)
+            if nargin == 0
+                SVD.modes = 80;
+            else
+                SVD.modes = modes;
+                SVD.originalInstanceSet = instanceSet;
+            end
+        end
+        
+        function SVD = compute(SVD)
+            tic
+            [U, S, V] = svd(SVD.originalInstanceSet.getInstances);
+            data_svd = U*S(:,1:SVD.modes)*V(1:SVD.modes,1:SVD.modes)';
+            [numInst, ~] = size(data_svd);
+            SVD.avgTime = toc/numInst;
+            SVD.filteredInstanceSet = eegtoolkit.util.InstanceSet(data_svd, SVD.originalInstanceSet.getLabels);
+        end
+        function configInfo = getConfigInfo(SVD)
+            configInfo = sprintf('SVD\tmodes:%d', SVD.modes);
+        end
+        
+        function time = getTime(SVD)
+            time = SVD.avgTime;
+        end
+    end
+end
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/graph.dot b/doc/+eegtoolkit/+featselection/@SVD/graph.dot
new file mode 100644
index 0000000..4c18e29
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  SVD -> SVD;
+
+  SVD [URL="SVD.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/graph.html b/doc/+eegtoolkit/+featselection/@SVD/graph.html
new file mode 100644
index 0000000..c601b51
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+featselection/@SVD</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@SVD">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@SVD">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+featselection/@SVD</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@SVD" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="SVD.html" title="SVD" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/graph.map b/doc/+eegtoolkit/+featselection/@SVD/graph.map
new file mode 100644
index 0000000..d61dd1c
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="SVD.html" title="SVD" alt="" coords="81,29,79,22,74,15,65,10,54,7,43,5,31,7,20,10,12,15,6,22,5,29,6,37,12,43,20,49,31,52,43,53,54,52,65,49,74,43,79,37">
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new file mode 100644
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diff --git a/doc/+eegtoolkit/+featselection/@SVD/index.html b/doc/+eegtoolkit/+featselection/@SVD/index.html
new file mode 100644
index 0000000..865923a
--- /dev/null
+++ b/doc/+eegtoolkit/+featselection/@SVD/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+featselection/@SVD</title>
+  <meta name="keywords" content="./+eegtoolkit/+featselection/@SVD">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@SVD">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+featselection/@SVD</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="SVD.html">SVD</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html
new file mode 100644
index 0000000..6491268
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html
@@ -0,0 +1,152 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Amuse</title>
+  <meta name="keywords" content="Amuse">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Amuse</a> &gt; Amuse.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Amuse
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Amuse.html" class="code" title="">Amuse</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Amuse.html" class="code" title="">Amuse</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function AM = Amuse()</a></li><li><a href="#_sub2" class="code">function out = process(AM,in )</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(AM)</a></li><li><a href="#_sub4" class="code">function time = getTime(AM)</a></li><li><a href="#_sub5" class="code">function [W,D1,y] = amuse(AM,X)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Amuse.m">Amuse.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Amuse.html" class="code" title="">Amuse</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     
+0003     properties
+0004         first;
+0005         last;
+0006         avgTime;
+0007     <span class="keyword">end</span>
+0008     
+0009     methods
+0010         <a name="_sub0" href="#_subfunctions" class="code">function AM = Amuse()</a>
+0011             AM.first = 2;
+0012             AM.last = 256;
+0013         <span class="keyword">end</span>
+0014         
+0015         <a name="_sub1" href="#_subfunctions" class="code">function out = process(AM,in )</a>
+0016             out = {};
+0017             total = 0;
+0018             <span class="keyword">for</span> i=1:length(in)
+0019                 <span class="comment">%                 i</span>
+0020                 <span class="comment">%                 in{i}.signal(end,:) = [];</span>
+0021                 tic
+0022                 signal = in{i}.signal;
+0023                 <span class="comment">%                 signal(end,:) = [];</span>
+0024                 [W,~,yest] = AM.amuse(signal);
+0025                 signal = pinv(W(AM.first:AM.last,:))*yest(AM.first:AM.last,: );
+0026                 total = total + toc;
+0027                 in{i}.signal = signal;
+0028                 <span class="comment">%                 out{i} = eegtoolkit.util.Trial(signal,in{i}.label,in{i}.samplingRate,in{i}.subjectid);</span>
+0029             <span class="keyword">end</span>
+0030             out = in;
+0031             <span class="comment">%             total = toc;</span>
+0032             AM.avgTime = total/length(in);
+0033         <span class="keyword">end</span>
+0034         
+0035         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(AM)</a>
+0036             configInfo = sprintf(<span class="string">'Amuse:\t%d-%d'</span>,AM.first,AM.last);
+0037         <span class="keyword">end</span>
+0038         
+0039         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(AM)</a>
+0040             time = AM.avgTime;
+0041         <span class="keyword">end</span>
+0042     <span class="keyword">end</span>
+0043     
+0044     methods (Access = private)
+0045         <a name="_sub4" href="#_subfunctions" class="code">function [W,D1,y] = amuse(AM,X)</a>
+0046             <span class="comment">% BSS using eigenvalue value decomposition</span>
+0047             <span class="comment">% Program written by A. Cichocki and R. Szupiluk</span>
+0048             <span class="comment">%</span>
+0049             <span class="comment">% X [m x N] matrix of observed (measured) signals,</span>
+0050             <span class="comment">% W separating matrix,</span>
+0051             <span class="comment">% y estimated separated sources</span>
+0052             <span class="comment">% p time delay used in computation of covariance matrices</span>
+0053             <span class="comment">% optimal time-delay default p= 1</span>
+0054             <span class="comment">%</span>
+0055             <span class="comment">% First stage: Standard prewhitening</span>
+0056             
+0057             [m,N]=size(X);
+0058             <span class="keyword">if</span> nargin==2,
+0059                 n=m; <span class="comment">%</span>
+0060             <span class="keyword">end</span>;
+0061             
+0062             Rxx=(X*X')/N;
+0063             
+0064             [Ux,Dx,Vx]=svd(Rxx);
+0065             Dx=diag(Dx);
+0066             <span class="comment">% n=xxx;</span>
+0067             <span class="keyword">if</span> n&lt;m, <span class="comment">% under assumption of additive white noise and</span>
+0068                 <span class="comment">%when the number of sources are known or can a priori estimated</span>
+0069                 Dx=Dx-real((mean(Dx(n+1:m))));
+0070                 Q= diag(real(sqrt(1./Dx(1:n))))*Ux(:,1:n)';
+0071                 <span class="comment">%</span>
+0072             <span class="keyword">else</span>    <span class="comment">% under assumption of no additive noise and when the</span>
+0073                 <span class="comment">% number of sources is unknown</span>
+0074                 n=max(find(Dx&gt;1e-199)); <span class="comment">%Detection the number of sources</span>
+0075                 Q= diag(real(sqrt(1./Dx(1:n))))*Ux(:,1:n)';
+0076             <span class="keyword">end</span>;
+0077 
+0078             <span class="comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span>
+0079             <span class="comment">% Second stage: Fast separation using sorting EVD</span>
+0080             <span class="comment">% notation the same as used in the Chapter 4</span>
+0081             Xb=Q*X;
+0082             p=1;
+0083             <span class="comment">% paramter p can take here value different than 1</span>
+0084             <span class="comment">% for example -1 or 2.</span>
+0085             N=max(size(Xb));
+0086             Xb=Xb-kron(mean(Xb')',ones(1,N));
+0087             
+0088             Rxbxbp=(Xb(:,1:N-1)*Xb(:,2:N)')/(N-1);
+0089             Rxbxbp= Rxbxbp+Rxbxbp';
+0090             [Vxb Dxb]=eig(Rxbxbp);
+0091             [D1 perm]=sort(diag(Dxb));
+0092             D1=flipud(D1);
+0093             Vxb=Vxb(:,flipud(perm));
+0094             W = Vxb'*Q;
+0095             y = Vxb' * Xb;<span class="comment">%change Xb instead of x1</span>
+0096         <span class="keyword">end</span>
+0097     <span class="keyword">end</span>
+0098     
+0099     
+0100     
+0101 <span class="keyword">end</span>
+0102</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.m b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.m
new file mode 100644
index 0000000..06e5302
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.m
@@ -0,0 +1,102 @@
+classdef Amuse < eegtoolkit.preprocessing.PreprocessingBase
+    
+    properties
+        first;
+        last;
+        avgTime;
+    end
+    
+    methods
+        function AM = Amuse()
+            AM.first = 2;
+            AM.last = 256;
+        end
+        
+        function out = process(AM,in )
+            out = {};
+            total = 0;
+            for i=1:length(in)
+                %                 i
+                %                 in{i}.signal(end,:) = [];
+                tic
+                signal = in{i}.signal;
+                %                 signal(end,:) = [];
+                [W,~,yest] = AM.amuse(signal);
+                signal = pinv(W(AM.first:AM.last,:))*yest(AM.first:AM.last,: );
+                total = total + toc;
+                in{i}.signal = signal;
+                %                 out{i} = eegtoolkit.util.Trial(signal,in{i}.label,in{i}.samplingRate,in{i}.subjectid);
+            end
+            out = in;
+            %             total = toc;
+            AM.avgTime = total/length(in);
+        end
+        
+        function configInfo = getConfigInfo(AM)
+            configInfo = sprintf('Amuse:\t%d-%d',AM.first,AM.last);
+        end
+        
+        function time = getTime(AM)
+            time = AM.avgTime;
+        end
+    end
+    
+    methods (Access = private)
+        function [W,D1,y] = amuse(AM,X)
+            % BSS using eigenvalue value decomposition
+            % Program written by A. Cichocki and R. Szupiluk
+            %
+            % X [m x N] matrix of observed (measured) signals,
+            % W separating matrix,
+            % y estimated separated sources
+            % p time delay used in computation of covariance matrices
+            % optimal time-delay default p= 1
+            %
+            % First stage: Standard prewhitening
+            
+            [m,N]=size(X);
+            if nargin==2,
+                n=m; %
+            end;
+            
+            Rxx=(X*X')/N;
+            
+            [Ux,Dx,Vx]=svd(Rxx);
+            Dx=diag(Dx);
+            % n=xxx;
+            if n<m, % under assumption of additive white noise and
+                %when the number of sources are known or can a priori estimated
+                Dx=Dx-real((mean(Dx(n+1:m))));
+                Q= diag(real(sqrt(1./Dx(1:n))))*Ux(:,1:n)';
+                %
+            else    % under assumption of no additive noise and when the
+                % number of sources is unknown
+                n=max(find(Dx>1e-199)); %Detection the number of sources
+                Q= diag(real(sqrt(1./Dx(1:n))))*Ux(:,1:n)';
+            end;
+
+            %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+            % Second stage: Fast separation using sorting EVD
+            % notation the same as used in the Chapter 4
+            Xb=Q*X;
+            p=1;
+            % paramter p can take here value different than 1
+            % for example -1 or 2.
+            N=max(size(Xb));
+            Xb=Xb-kron(mean(Xb')',ones(1,N));
+            
+            Rxbxbp=(Xb(:,1:N-1)*Xb(:,2:N)')/(N-1);
+            Rxbxbp= Rxbxbp+Rxbxbp';
+            [Vxb Dxb]=eig(Rxbxbp);
+            [D1 perm]=sort(diag(Dxb));
+            D1=flipud(D1);
+            Vxb=Vxb(:,flipud(perm));
+            W = Vxb'*Q;
+            y = Vxb' * Xb;%change Xb instead of x1
+        end
+    end
+    
+    
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.dot b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.dot
new file mode 100644
index 0000000..8736430
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Amuse -> Amuse;
+
+  Amuse [URL="Amuse.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html
new file mode 100644
index 0000000..48d9378
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@Amuse</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@Amuse">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Amuse">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Amuse</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Amuse" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Amuse.html" title="Amuse" alt="" coords="102,29,99,22,93,15,82,10,68,7,53,5,38,7,25,10,14,15,7,22,5,29,7,37,14,43,25,49,38,52,53,53,68,52,82,49,93,43,99,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.map b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.map
new file mode 100644
index 0000000..92cf9a4
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="Amuse.html" title="Amuse" alt="" coords="102,29,99,22,93,15,82,10,68,7,53,5,38,7,25,10,14,15,7,22,5,29,7,37,14,43,25,49,38,52,53,53,68,52,82,49,93,43,99,37">
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.png b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.png
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diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/index.html b/doc/+eegtoolkit/+preprocessing/@Amuse/index.html
new file mode 100644
index 0000000..b5a54a5
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@Amuse</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@Amuse">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Amuse">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@Amuse</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Amuse.html">Amuse</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html
new file mode 100644
index 0000000..76b4074
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html
@@ -0,0 +1,100 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of DigitalFilter</title>
+  <meta name="keywords" content="DigitalFilter">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@DigitalFilter</a> &gt; DigitalFilter.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>DigitalFilter
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="DigitalFilter.html" class="code" title="">DigitalFilter</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="DigitalFilter.html" class="code" title="">DigitalFilter</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function DF = DigitalFilter(filt)</a></li><li><a href="#_sub2" class="code">function out = process(DF,in )</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(DF)</a></li><li><a href="#_sub4" class="code">function time = getTime(DF)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="DigitalFilter.m">DigitalFilter.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="DigitalFilter.html" class="code" title="">DigitalFilter</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     properties
+0003         filt;
+0004         info;
+0005         avgTime;
+0006     <span class="keyword">end</span>
+0007     
+0008     methods
+0009         <a name="_sub0" href="#_subfunctions" class="code">function DF = DigitalFilter(filt)</a>
+0010             <span class="keyword">if</span>(nargin &gt; 0)
+0011                 DF.filt = filt;
+0012             <span class="keyword">end</span>
+0013         <span class="keyword">end</span>
+0014         
+0015         <a name="_sub1" href="#_subfunctions" class="code">function out = process(DF,in )</a>
+0016             tic;
+0017             <span class="keyword">for</span> i=1:length(in)
+0018 <span class="comment">%                 i</span>
+0019                 signal = in{i}.signal;
+0020                 [numChannels, ~] = size(signal);
+0021                 <span class="keyword">for</span> j=1:numChannels
+0022                     <span class="keyword">if</span> isa(DF.filt,<span class="string">'dfilt.df2sos'</span>) || isa(DF.filt,<span class="string">'dfilt.df2'</span>)
+0023 <span class="comment">%                         signal(j,:) = filter(DF.filt,signal(j,:));</span>
+0024                         signal(j,:) = filtfilt(DF.filt.sosMatrix,DF.filt.ScaleValues,signal(j,:));
+0025                     <span class="keyword">elseif</span> isa(DF.filt,<span class="string">'dfilt.dffir'</span>)
+0026                         signal(j,:) = filtfilt(DF.filt.Numerator,1,signal(j,:));
+0027                     <span class="keyword">end</span>
+0028                 <span class="keyword">end</span>
+0029                   in{i}.signal = signal;
+0030             <span class="keyword">end</span>
+0031             out = in;
+0032             total = toc;
+0033             DF.avgTime = total/length(in);
+0034         <span class="keyword">end</span>
+0035         
+0036         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(DF)</a>
+0037             <span class="keyword">if</span> isempty(DF.info)
+0038                 configInfo = <span class="string">'DigitalFilter'</span>;
+0039             <span class="keyword">else</span>
+0040                 configInfo = strcat(<span class="string">'DigitalFilter:\t'</span>,info);
+0041             <span class="keyword">end</span>
+0042         <span class="keyword">end</span>
+0043         
+0044         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(DF)</a>
+0045             time = DF.avgTime;
+0046         <span class="keyword">end</span>
+0047     <span class="keyword">end</span>
+0048     
+0049 <span class="keyword">end</span>
+0050</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.m b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.m
new file mode 100644
index 0000000..e3390be
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.m
@@ -0,0 +1,50 @@
+classdef DigitalFilter < eegtoolkit.preprocessing.PreprocessingBase
+    properties
+        filt;
+        info;
+        avgTime;
+    end
+    
+    methods
+        function DF = DigitalFilter(filt)
+            if(nargin > 0)
+                DF.filt = filt;
+            end
+        end
+        
+        function out = process(DF,in )
+            tic;
+            for i=1:length(in)
+%                 i
+                signal = in{i}.signal;
+                [numChannels, ~] = size(signal);
+                for j=1:numChannels
+                    if isa(DF.filt,'dfilt.df2sos') || isa(DF.filt,'dfilt.df2')
+%                         signal(j,:) = filter(DF.filt,signal(j,:));
+                        signal(j,:) = filtfilt(DF.filt.sosMatrix,DF.filt.ScaleValues,signal(j,:));
+                    elseif isa(DF.filt,'dfilt.dffir')
+                        signal(j,:) = filtfilt(DF.filt.Numerator,1,signal(j,:));
+                    end
+                end
+                  in{i}.signal = signal;
+            end
+            out = in;
+            total = toc;
+            DF.avgTime = total/length(in);
+        end
+        
+        function configInfo = getConfigInfo(DF)
+            if isempty(DF.info)
+                configInfo = 'DigitalFilter';
+            else
+                configInfo = strcat('DigitalFilter:\t',info);
+            end
+        end
+        
+        function time = getTime(DF)
+            time = DF.avgTime;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.dot b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.dot
new file mode 100644
index 0000000..ef63f77
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  DigitalFilter -> DigitalFilter;
+
+  DigitalFilter [URL="DigitalFilter.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html
new file mode 100644
index 0000000..7a752d9
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@DigitalFilter</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@DigitalFilter</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@DigitalFilter" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="DigitalFilter.html" title="DigitalFilter" alt="" coords="148,29,144,22,134,15,118,10,98,7,76,5,54,7,34,10,18,15,8,22,4,29,8,37,18,43,34,49,54,52,76,53,98,52,118,49,134,43,144,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.map b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.map
new file mode 100644
index 0000000..7c4f4d2
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="DigitalFilter.html" title="DigitalFilter" alt="" coords="148,29,144,22,134,15,118,10,98,7,76,5,54,7,34,10,18,15,8,22,4,29,8,37,18,43,34,49,54,52,76,53,98,52,118,49,134,43,144,37">
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diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/index.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/index.html
new file mode 100644
index 0000000..1c179ac
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@DigitalFilter</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@DigitalFilter</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="DigitalFilter.html">DigitalFilter</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html
new file mode 100644
index 0000000..90734ba
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html
@@ -0,0 +1,97 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FastICA</title>
+  <meta name="keywords" content="FastICA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@FastICA</a> &gt; FastICA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FastICA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FastICA.html" class="code" title="">FastICA</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FastICA.html" class="code" title="">FastICA</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function ICA = FastICA()</a></li><li><a href="#_sub2" class="code">function out = process(ICA,in )</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(ICA)</a></li><li><a href="#_sub4" class="code">function time = getTime(ICA)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FastICA.m">FastICA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="FastICA.html" class="code" title="">FastICA</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     
+0003     properties
+0004         first;
+0005         last;
+0006         avgTime;
+0007     <span class="keyword">end</span>
+0008     
+0009     methods
+0010         <a name="_sub0" href="#_subfunctions" class="code">function ICA = FastICA()</a>
+0011             ICA.first = 2;
+0012             ICA.last = 256;
+0013         <span class="keyword">end</span>
+0014         
+0015         <a name="_sub1" href="#_subfunctions" class="code">function out = process(ICA,in )</a>
+0016             out = {};
+0017             total = 0;
+0018             <span class="keyword">for</span> i=1:length(in)
+0019                 i
+0020 <span class="comment">%                 in{i}.signal(end,:) = [];</span>
+0021                 tic
+0022                 signal = in{i}.signal;
+0023 <span class="comment">%                 signal(end,:) = [];</span>
+0024 <span class="comment">%                 [W,~,yest] = amuse(signal);</span>
+0025 <span class="comment">%                 signal = pinv(W(ICA.first:ICA.last,:))*yest(ICA.first:ICA.last,: );</span>
+0026                 [icasig, A, W] = fastica (signal);
+0027                 signal = A(:,ICA.first:end)*icasig(ICA.first:<span class="keyword">end</span>,:);
+0028                 total = total + toc;
+0029 <span class="comment">%                 in{i}.signal = signal;</span>
+0030                 out{i} = eegtoolkit.util.Trial(signal,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid,in{i}.type);
+0031             <span class="keyword">end</span>
+0032 <span class="comment">%             out = in;</span>
+0033 <span class="comment">%             total = toc;</span>
+0034             ICA.avgTime = total/length(in);
+0035         <span class="keyword">end</span>
+0036         
+0037         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(ICA)</a>
+0038             configInfo = sprintf(<span class="string">'FastICA:\t%d-%d'</span>,ICA.first,ICA.last);
+0039         <span class="keyword">end</span>
+0040         
+0041         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(ICA)</a>
+0042             time = ICA.avgTime;
+0043         <span class="keyword">end</span>
+0044     <span class="keyword">end</span>
+0045     
+0046 <span class="keyword">end</span>
+0047</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.m b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.m
new file mode 100644
index 0000000..dbc3ac3
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.m
@@ -0,0 +1,47 @@
+classdef FastICA < eegtoolkit.preprocessing.PreprocessingBase
+    
+    properties
+        first;
+        last;
+        avgTime;
+    end
+    
+    methods
+        function ICA = FastICA()
+            ICA.first = 2;
+            ICA.last = 256;
+        end
+        
+        function out = process(ICA,in )
+            out = {};
+            total = 0;
+            for i=1:length(in)
+                i
+%                 in{i}.signal(end,:) = [];
+                tic
+                signal = in{i}.signal;
+%                 signal(end,:) = [];
+%                 [W,~,yest] = amuse(signal);
+%                 signal = pinv(W(ICA.first:ICA.last,:))*yest(ICA.first:ICA.last,: );
+                [icasig, A, W] = fastica (signal);
+                signal = A(:,ICA.first:end)*icasig(ICA.first:end,:);
+                total = total + toc;
+%                 in{i}.signal = signal;
+                out{i} = eegtoolkit.util.Trial(signal,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid,in{i}.type);
+            end
+%             out = in;
+%             total = toc;
+            ICA.avgTime = total/length(in);
+        end
+        
+        function configInfo = getConfigInfo(ICA)
+            configInfo = sprintf('FastICA:\t%d-%d',ICA.first,ICA.last);
+        end
+        
+        function time = getTime(ICA)
+            time = ICA.avgTime;
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/graph.dot b/doc/+eegtoolkit/+preprocessing/@FastICA/graph.dot
new file mode 100644
index 0000000..22490a9
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FastICA -> FastICA;
+
+  FastICA [URL="FastICA.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html b/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html
new file mode 100644
index 0000000..a8abb55
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@FastICA</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@FastICA">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@FastICA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@FastICA</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@FastICA" border="2" style="color:#000;">  
+<map name="mainmap">
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+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
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diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/index.html b/doc/+eegtoolkit/+preprocessing/@FastICA/index.html
new file mode 100644
index 0000000..0360c09
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@FastICA</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@FastICA">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@FastICA">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@FastICA</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FastICA.html">FastICA</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html
new file mode 100644
index 0000000..87198d7
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html
@@ -0,0 +1,95 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of PreprocessingBase</title>
+  <meta name="keywords" content="PreprocessingBase">
+  <meta name="description" content="Abstract class for preprocessing. Implement the functions for any">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@PreprocessingBase</a> &gt; PreprocessingBase.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>PreprocessingBase
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>Abstract class for preprocessing. Implement the functions for any</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Abstract class for preprocessing. Implement the functions for any
+ preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+ rereferencing, etc.
+ 
+ Properties:
+ originalTrials: cell array with the trials to be processed
+ processedTrials: the processed trials to be returned
+ 
+ Functions:
+Implement this function to process the in trials and return the processed
+trials (out)
+   out = obj.process(in);
+Info &amp; run time so that the experiments are easily documented. configInfo
+is a string with the configuration information and time is of type double.
+   configInfo = obj.getConfigInfo();
+   time = obj.getTime();</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PreprocessingBase.html" class="code" title="">PreprocessingBase</a>	Abstract class for preprocessing. Implement the functions for any</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="PreprocessingBase.html" class="code" title="">PreprocessingBase</a>	Abstract class for preprocessing. Implement the functions for any</li></ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="PreprocessingBase.m">PreprocessingBase.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Abstract class for preprocessing. Implement the functions for any</span>
+0002 <span class="comment">% preprocessing step (e.g. filtering, artifact removal, sub-sampling,</span>
+0003 <span class="comment">% rereferencing, etc.</span>
+0004 <span class="comment">%</span>
+0005 <span class="comment">% Properties:</span>
+0006 <span class="comment">% originalTrials: cell array with the trials to be processed</span>
+0007 <span class="comment">% processedTrials: the processed trials to be returned</span>
+0008 <span class="comment">%</span>
+0009 <span class="comment">% Functions:</span>
+0010 <span class="comment">%Implement this function to process the in trials and return the processed</span>
+0011 <span class="comment">%trials (out)</span>
+0012 <span class="comment">%   out = obj.process(in);</span>
+0013 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0014 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0015 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0016 <span class="comment">%   time = obj.getTime();</span>
+0017 
+0018 classdef <a href="PreprocessingBase.html" class="code" title="">PreprocessingBase</a> &lt; handle
+0019     
+0020     properties
+0021         originalTrials;
+0022         processedTrials;
+0023     <span class="keyword">end</span>
+0024     
+0025     methods (Abstract = true)
+0026         out = process(obj,in);
+0027         configInfo = getConfigInfo(obj);
+0028         time = getTime(obj);
+0029     <span class="keyword">end</span>
+0030     
+0031 <span class="keyword">end</span>
+0032</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m
new file mode 100644
index 0000000..9abae63
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.m
@@ -0,0 +1,32 @@
+% Abstract class for preprocessing. Implement the functions for any
+% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
+% rereferencing, etc.
+% 
+% Properties:
+% originalTrials: cell array with the trials to be processed
+% processedTrials: the processed trials to be returned
+% 
+% Functions:
+%Implement this function to process the in trials and return the processed
+%trials (out)
+%   out = obj.process(in);
+%Info & run time so that the experiments are easily documented. configInfo
+%is a string with the configuration information and time is of type double.
+%   configInfo = obj.getConfigInfo();
+%   time = obj.getTime();
+
+classdef PreprocessingBase < handle
+    
+    properties
+        originalTrials;
+        processedTrials;
+    end
+    
+    methods (Abstract = true)
+        out = process(obj,in);
+        configInfo = getConfigInfo(obj);
+        time = getTime(obj);
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.dot b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.dot
new file mode 100644
index 0000000..c7affe5
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  PreprocessingBase -> PreprocessingBase;
+
+  PreprocessingBase [URL="PreprocessingBase.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.html
new file mode 100644
index 0000000..e0191c3
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="PreprocessingBase.html" title="PreprocessingBase" alt="" coords="211,29,206,22,191,15,169,10,140,7,108,5,76,7,47,10,25,15,10,22,5,29,10,37,25,43,47,49,76,52,108,53,140,52,169,49,191,43,206,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.map b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.map
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diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/index.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/index.html
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@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@PreprocessingBase</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="PreprocessingBase.html">PreprocessingBase</a></td><td>Abstract class for preprocessing. Implement the functions for any </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Rereferencing</title>
+  <meta name="keywords" content="Rereferencing">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Rereferencing</a> &gt; Rereferencing.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Rereferencing
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Rereferencing.html" class="code" title="">Rereferencing</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Rereferencing.html" class="code" title="">Rereferencing</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function RR = Rereferencing()</a></li><li><a href="#_sub2" class="code">function out = process(RR,in)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(RR)</a></li><li><a href="#_sub4" class="code">function time = getTime(RR)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Rereferencing.m">Rereferencing.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Rereferencing.html" class="code" title="">Rereferencing</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     
+0003     properties
+0004         <span class="comment">%meanSignal=1: Subtract the mean from the signal</span>
+0005         <span class="comment">%meanSignal=2: Average rereferencing</span>
+0006         meanSignal;
+0007         avgTime;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods
+0011         <a name="_sub0" href="#_subfunctions" class="code">function RR = Rereferencing()</a>
+0012             RR.meanSignal = 1;
+0013         <span class="keyword">end</span>
+0014         
+0015         <a name="_sub1" href="#_subfunctions" class="code">function out = process(RR,in)</a>
+0016             out = {};
+0017             tic;
+0018             <span class="keyword">for</span> i=1:length(in)
+0019                 <span class="keyword">if</span> RR.meanSignal == 1
+0020                     [numChannels,~] = size(in{i}.signal);
+0021                     <span class="keyword">for</span> j=1:numChannels
+0022                         in{i}.signal(j,:) = in{i}.signal(j,:) - mean(in{i}.signal(j,:));
+0023                     <span class="keyword">end</span>
+0024                 <span class="keyword">elseif</span> RR.meanSignal == 2
+0025                     meanChann = mean(in{i}.signal);
+0026                       in{i}.signal = in{i}.signal-repmat(meanChann,257,1);
+0027                 <span class="keyword">end</span>
+0028                 out = in;
+0029             <span class="keyword">end</span>
+0030             RR.avgTime = toc/length(in);
+0031         <span class="keyword">end</span>
+0032         
+0033         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(RR)</a>
+0034             configInfo = sprintf(<span class="string">'Rereferencing:\tmeanSignal:%d'</span>,RR.meanSignal);
+0035         <span class="keyword">end</span>
+0036         
+0037                         
+0038         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(RR)</a>
+0039             time = RR.avgTime;
+0040         <span class="keyword">end</span>
+0041         
+0042     <span class="keyword">end</span>
+0043     
+0044 <span class="keyword">end</span>
+0045</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.m b/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.m
new file mode 100644
index 0000000..06c48e7
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.m
@@ -0,0 +1,45 @@
+classdef Rereferencing < eegtoolkit.preprocessing.PreprocessingBase
+    
+    properties
+        %meanSignal=1: Subtract the mean from the signal
+        %meanSignal=2: Average rereferencing
+        meanSignal;
+        avgTime;
+    end
+    
+    methods
+        function RR = Rereferencing()
+            RR.meanSignal = 1;
+        end
+        
+        function out = process(RR,in)
+            out = {};
+            tic;
+            for i=1:length(in)
+                if RR.meanSignal == 1
+                    [numChannels,~] = size(in{i}.signal);
+                    for j=1:numChannels
+                        in{i}.signal(j,:) = in{i}.signal(j,:) - mean(in{i}.signal(j,:));
+                    end
+                elseif RR.meanSignal == 2
+                    meanChann = mean(in{i}.signal);
+                      in{i}.signal = in{i}.signal-repmat(meanChann,257,1);
+                end
+                out = in;
+            end
+            RR.avgTime = toc/length(in);
+        end
+        
+        function configInfo = getConfigInfo(RR)
+            configInfo = sprintf('Rereferencing:\tmeanSignal:%d',RR.meanSignal);
+        end
+        
+                        
+        function time = getTime(RR)
+            time = RR.avgTime;
+        end
+        
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.dot b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.dot
new file mode 100644
index 0000000..03cfa28
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Rereferencing -> Rereferencing;
+
+  Rereferencing [URL="Rereferencing.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.html
new file mode 100644
index 0000000..c91e1a3
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@Rereferencing</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@Rereferencing">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Rereferencing">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Rereferencing</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Rereferencing" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Rereferencing.html" title="Rereferencing" alt="" coords="166,29,162,22,151,15,133,10,110,7,85,5,60,7,38,10,20,15,9,22,5,29,9,37,20,43,38,49,60,52,85,53,110,52,133,49,151,43,162,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.map b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.map
new file mode 100644
index 0000000..9e51d40
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/index.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/index.html
new file mode 100644
index 0000000..b56a4f6
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Rereferencing/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@Rereferencing</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@Rereferencing">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Rereferencing">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@Rereferencing</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Rereferencing.html">Rereferencing</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html
new file mode 100644
index 0000000..3b1cfb2
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html
@@ -0,0 +1,143 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of SampleSelection</title>
+  <meta name="keywords" content="SampleSelection">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@SampleSelection</a> &gt; SampleSelection.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>SampleSelection
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SampleSelection.html" class="code" title="">SampleSelection</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="SampleSelection.html" class="code" title="">SampleSelection</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CS = SampleSelection(channels,sampleRange)</a></li><li><a href="#_sub2" class="code">function out = process(CS,in)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CS)</a></li><li><a href="#_sub4" class="code">function time = getTime(CS)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="SampleSelection.m">SampleSelection.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="SampleSelection.html" class="code" title="">SampleSelection</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     properties
+0003         channels;
+0004         sampleRange;
+0005         samplingRate;
+0006     <span class="keyword">end</span>
+0007     
+0008     methods
+0009         <a name="_sub0" href="#_subfunctions" class="code">function CS = SampleSelection(channels,sampleRange)</a>
+0010             <span class="keyword">if</span>(nargin == 0)
+0011                 CS.channels = 126;
+0012                 CS.sampleRange = [1,1250];
+0013             <span class="keyword">end</span>
+0014             <span class="keyword">if</span>(nargin &gt; 0)
+0015                 CS.channels = channels;
+0016             <span class="keyword">end</span>
+0017             <span class="keyword">if</span> nargin &gt; 1
+0018                 CS.sampleRange = sampleRange;
+0019             <span class="keyword">end</span>
+0020         <span class="keyword">end</span>
+0021         
+0022         <a name="_sub1" href="#_subfunctions" class="code">function out = process(CS,in)</a>
+0023             out = {};
+0024             CS.samplingRate = in{1}.samplingRate;
+0025             <span class="keyword">for</span> i=1:length(in)
+0026                 <span class="keyword">if</span>(length(CS.channels) &gt; 0)
+0027                     <span class="keyword">if</span>(length(CS.sampleRange) &gt; 2)
+0028                         signal = in{i}.signal(CS.channels,CS.sampleRange);
+0029                         out{i} = eegtoolkit.util.Trial(signal <span class="keyword">...</span>
+0030                             ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+0031                     <span class="keyword">elseif</span>(length(CS.sampleRange) &gt; 0)
+0032                         <span class="comment">%channels AND sampleRange</span>
+0033                         signal = in{i}.signal(CS.channels,CS.sampleRange(1):CS.sampleRange(2));
+0034                         out{i} = eegtoolkit.util.Trial(signal <span class="keyword">...</span>
+0035                             ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+0036                     <span class="keyword">else</span>
+0037                         <span class="comment">%ONLY channels</span>
+0038                         signal = in{i}.signal(CS.channels,:);
+0039                         out{i} = eegtoolkit.util.Trial(signal <span class="keyword">...</span>
+0040                             ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+0041                     <span class="keyword">end</span>
+0042                 <span class="keyword">else</span>
+0043                     <span class="keyword">if</span>(length(CS.sampleRange) &gt; 2)
+0044                         signal = in{i}.signal(:,CS.sampleRange);
+0045                         out{i} = eegtoolkit.util.Trial(signal <span class="keyword">...</span>
+0046                             ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+0047                     <span class="keyword">elseif</span>(length(CS.sampleRange) &gt; 0)
+0048                         <span class="comment">%ONLY sampleRange</span>
+0049                         signal = in{i}.signal(:,CS.sampleRange(1):CS.sampleRange(2));
+0050                         out{i} = eegtoolkit.util.Trial(signal <span class="keyword">...</span>
+0051                             ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+0052                     <span class="keyword">else</span>
+0053                         <span class="comment">%NOTHING (?)</span>
+0054                         disp(<span class="string">'Warning: No parameter specified for SampleSelection, using all channels and samples'</span>);
+0055                     <span class="keyword">end</span>
+0056                 <span class="keyword">end</span>
+0057             <span class="keyword">end</span>
+0058         <span class="keyword">end</span>
+0059         
+0060         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CS)</a>
+0061             <span class="keyword">if</span>(length(CS.channels) &gt; 0)
+0062                 <span class="keyword">if</span>(length(CS.sampleRange) &gt; 0)
+0063                     configInfo = <span class="string">'SampleSelection\tChannels:'</span>;
+0064                     <span class="keyword">for</span> i=1:length(CS.channels)
+0065                         configInfo = strcat(configInfo,sprintf(<span class="string">'%d+'</span>,CS.channels(i)));
+0066                     <span class="keyword">end</span>
+0067                     configInfo = strcat(configInfo,sprintf(<span class="string">'\tsampleRange:%d-%d'</span>,CS.sampleRange(1),CS.sampleRange(2)));
+0068                 <span class="keyword">else</span>
+0069                     configInfo = <span class="string">'SampleSelection\tChannels:'</span>;
+0070                     <span class="keyword">for</span> i=1:length(CS.channels)
+0071                         configInfo = strcat(configInfo,sprintf(<span class="string">'%d+'</span>,CS.channels(i)));
+0072                     <span class="keyword">end</span>
+0073                 <span class="keyword">end</span>
+0074             <span class="keyword">else</span>
+0075                 <span class="keyword">if</span>(length(CS.sampleRange) &gt; 0)
+0076                     configInfo = sprintf(<span class="string">'SampleSelection\tSampleRange:%d-%d'</span>,CS.sampleRange(1),CS.sampleRange(2));
+0077                     <span class="comment">%ONLY sampleRange</span>
+0078                 <span class="keyword">else</span>
+0079                     <span class="comment">%NOTHING (?)</span>
+0080                     configInfo = sprintf(<span class="string">'SampleSelection\tNothing specified'</span>);
+0081                 <span class="keyword">end</span>
+0082             <span class="keyword">end</span>
+0083         <span class="keyword">end</span>
+0084         
+0085         
+0086         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(CS)</a>
+0087             time = 0;
+0088         <span class="keyword">end</span>
+0089         
+0090     <span class="keyword">end</span>
+0091     
+0092 <span class="keyword">end</span>
+0093</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.m b/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.m
new file mode 100644
index 0000000..fad7d87
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.m
@@ -0,0 +1,93 @@
+classdef SampleSelection < eegtoolkit.preprocessing.PreprocessingBase
+    properties
+        channels;
+        sampleRange;
+        samplingRate;
+    end
+    
+    methods
+        function CS = SampleSelection(channels,sampleRange)
+            if(nargin == 0)
+                CS.channels = 126;
+                CS.sampleRange = [1,1250];
+            end
+            if(nargin > 0)
+                CS.channels = channels;
+            end
+            if nargin > 1
+                CS.sampleRange = sampleRange;
+            end
+        end
+        
+        function out = process(CS,in)
+            out = {};
+            CS.samplingRate = in{1}.samplingRate;
+            for i=1:length(in)
+                if(length(CS.channels) > 0)
+                    if(length(CS.sampleRange) > 2)
+                        signal = in{i}.signal(CS.channels,CS.sampleRange);
+                        out{i} = eegtoolkit.util.Trial(signal ...
+                            ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+                    elseif(length(CS.sampleRange) > 0)
+                        %channels AND sampleRange
+                        signal = in{i}.signal(CS.channels,CS.sampleRange(1):CS.sampleRange(2));
+                        out{i} = eegtoolkit.util.Trial(signal ...
+                            ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+                    else
+                        %ONLY channels
+                        signal = in{i}.signal(CS.channels,:);
+                        out{i} = eegtoolkit.util.Trial(signal ...
+                            ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+                    end
+                else
+                    if(length(CS.sampleRange) > 2)
+                        signal = in{i}.signal(:,CS.sampleRange);
+                        out{i} = eegtoolkit.util.Trial(signal ...
+                            ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+                    elseif(length(CS.sampleRange) > 0)
+                        %ONLY sampleRange
+                        signal = in{i}.signal(:,CS.sampleRange(1):CS.sampleRange(2));
+                        out{i} = eegtoolkit.util.Trial(signal ...
+                            ,in{i}.label,in{i}.samplingRate,in{i}.subjectid,in{i}.sessionid);
+                    else
+                        %NOTHING (?)
+                        disp('Warning: No parameter specified for SampleSelection, using all channels and samples');
+                    end
+                end
+            end
+        end
+        
+        function configInfo = getConfigInfo(CS)
+            if(length(CS.channels) > 0)
+                if(length(CS.sampleRange) > 0)
+                    configInfo = 'SampleSelection\tChannels:';
+                    for i=1:length(CS.channels)
+                        configInfo = strcat(configInfo,sprintf('%d+',CS.channels(i)));
+                    end
+                    configInfo = strcat(configInfo,sprintf('\tsampleRange:%d-%d',CS.sampleRange(1),CS.sampleRange(2)));
+                else
+                    configInfo = 'SampleSelection\tChannels:';
+                    for i=1:length(CS.channels)
+                        configInfo = strcat(configInfo,sprintf('%d+',CS.channels(i)));
+                    end
+                end
+            else
+                if(length(CS.sampleRange) > 0)
+                    configInfo = sprintf('SampleSelection\tSampleRange:%d-%d',CS.sampleRange(1),CS.sampleRange(2));
+                    %ONLY sampleRange
+                else
+                    %NOTHING (?)
+                    configInfo = sprintf('SampleSelection\tNothing specified');
+                end
+            end
+        end
+        
+        
+        function time = getTime(CS)
+            time = 0;
+        end
+        
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.dot b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.dot
new file mode 100644
index 0000000..f1cd68a
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  SampleSelection -> SampleSelection;
+
+  SampleSelection [URL="SampleSelection.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.html
new file mode 100644
index 0000000..6bad530
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@SampleSelection</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@SampleSelection">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@SampleSelection">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@SampleSelection</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@SampleSelection" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="SampleSelection.html" title="SampleSelection" alt="" coords="192,29,188,22,174,15,154,10,128,7,99,5,70,7,44,10,23,15,10,22,5,29,10,37,23,43,44,49,70,52,99,53,128,52,154,49,174,43,188,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.map b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.map
new file mode 100644
index 0000000..03d491b
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/index.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/index.html
new file mode 100644
index 0000000..95496df
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@SampleSelection/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@SampleSelection</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@SampleSelection">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@SampleSelection">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@SampleSelection</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="SampleSelection.html">SampleSelection</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.html
new file mode 100644
index 0000000..33241d4
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.html
@@ -0,0 +1,114 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Windsorize</title>
+  <meta name="keywords" content="Windsorize">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Windsorize</a> &gt; Windsorize.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Windsorize
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Windsorize.html" class="code" title="">Windsorize</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Windsorize.html" class="code" title="">Windsorize</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function obj = Windsorize(low,high)</a></li><li><a href="#_sub2" class="code">function trials = process(obj,trials)</a></li><li><a href="#_sub3" class="code">function configInfo = getConfigInfo(CS)</a></li><li><a href="#_sub4" class="code">function time = getTime(CS)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Windsorize.m">Windsorize.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="Windsorize.html" class="code" title="">Windsorize</a> &lt; eegtoolkit.preprocessing.PreprocessingBase
+0002     properties
+0003         limit_l;
+0004         limit_h;
+0005         subjectids;
+0006     <span class="keyword">end</span>
+0007     
+0008     methods
+0009         <a name="_sub0" href="#_subfunctions" class="code">function obj = Windsorize(low,high)</a>
+0010             <span class="keyword">if</span> nargin == 0
+0011                 obj.limit_l = 0.05;
+0012                 obj.limit_h = 0.95;
+0013             <span class="keyword">elseif</span> nargin == 2
+0014                 obj.limit_l = low;
+0015                 obj.limit_h = high;
+0016             <span class="keyword">else</span>
+0017                 error(<span class="string">'2 inputs are required for windsorize, the low and high limits'</span>);
+0018             <span class="keyword">end</span>
+0019         <span class="keyword">end</span>
+0020         
+0021         <a name="_sub1" href="#_subfunctions" class="code">function trials = process(obj,trials)</a>
+0022             subs = unique(obj.subjectids);
+0023             nchannels = size(trials{1}.signal,1);
+0024             trial_length = size(trials{1}.signal,2);
+0025             <span class="keyword">for</span> i=1:numel(subs)
+0026                 ids = find(obj.subjectids == subs(i));
+0027                 ntrials = numel(ids);
+0028                 <span class="comment">% Concatenate signal</span>
+0029                 signal = [];
+0030                 <span class="keyword">for</span> j=1:numel(ids)
+0031                     signal = [signal trials{ids(j)}.signal];
+0032                 <span class="keyword">end</span>
+0033                 <span class="comment">%windsorize</span>
+0034                 sorted_sig = sort(signal,2);
+0035                 upbound = sorted_sig(:,round(obj.limit_h*size(signal,2)));
+0036                 uprep = sorted_sig(:,round(obj.limit_h*size(signal,2))-1);
+0037                 lowbound = sorted_sig(:,round(obj.limit_l*size(signal,2)));
+0038                 lowrep = sorted_sig(:,round(obj.limit_l*size(signal,2))+1);
+0039                 <span class="keyword">for</span> ch=1:nchannels
+0040                     signal(ch,signal(ch,:)&gt;upbound(ch)) = uprep(ch);
+0041                     signal(ch,signal(ch,:)&lt;lowbound(ch)) = lowrep(ch);
+0042                 <span class="keyword">end</span>
+0043                 temp = mat2cell(signal,nchannels,trial_length*ones(ntrials,1));
+0044                 <span class="keyword">for</span> j=1:numel(ids)
+0045                     trials{ids(j)}.signal = temp{j};
+0046                 <span class="keyword">end</span>
+0047             <span class="keyword">end</span>
+0048             
+0049         <span class="keyword">end</span>
+0050         
+0051         
+0052         <a name="_sub2" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CS)</a>
+0053             configInfo = sprintf(<span class="string">'Windsorizing\tLow limit: %f, High limit: %f'</span>,CS.limit_l,CS.limit_l);
+0054         <span class="keyword">end</span>
+0055         
+0056         
+0057         <a name="_sub3" href="#_subfunctions" class="code">function time = getTime(CS)</a>
+0058             time = 0;
+0059         <span class="keyword">end</span>
+0060         
+0061     <span class="keyword">end</span>
+0062     
+0063 <span class="keyword">end</span>
+0064</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.m b/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.m
new file mode 100644
index 0000000..6aafe6d
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.m
@@ -0,0 +1,64 @@
+classdef Windsorize < eegtoolkit.preprocessing.PreprocessingBase
+    properties
+        limit_l;
+        limit_h;
+        subjectids;
+    end
+    
+    methods
+        function obj = Windsorize(low,high)
+            if nargin == 0
+                obj.limit_l = 0.05;
+                obj.limit_h = 0.95;
+            elseif nargin == 2
+                obj.limit_l = low;
+                obj.limit_h = high;
+            else
+                error('2 inputs are required for windsorize, the low and high limits');
+            end
+        end
+        
+        function trials = process(obj,trials)
+            subs = unique(obj.subjectids);
+            nchannels = size(trials{1}.signal,1);
+            trial_length = size(trials{1}.signal,2);
+            for i=1:numel(subs)
+                ids = find(obj.subjectids == subs(i));
+                ntrials = numel(ids);
+                % Concatenate signal
+                signal = [];
+                for j=1:numel(ids)
+                    signal = [signal trials{ids(j)}.signal];
+                end
+                %windsorize
+                sorted_sig = sort(signal,2);
+                upbound = sorted_sig(:,round(obj.limit_h*size(signal,2)));
+                uprep = sorted_sig(:,round(obj.limit_h*size(signal,2))-1);
+                lowbound = sorted_sig(:,round(obj.limit_l*size(signal,2)));
+                lowrep = sorted_sig(:,round(obj.limit_l*size(signal,2))+1);
+                for ch=1:nchannels
+                    signal(ch,signal(ch,:)>upbound(ch)) = uprep(ch);
+                    signal(ch,signal(ch,:)<lowbound(ch)) = lowrep(ch);
+                end
+                temp = mat2cell(signal,nchannels,trial_length*ones(ntrials,1));
+                for j=1:numel(ids)
+                    trials{ids(j)}.signal = temp{j};
+                end
+            end
+            
+        end
+        
+        
+        function configInfo = getConfigInfo(CS)
+            configInfo = sprintf('Windsorizing\tLow limit: %f, High limit: %f',CS.limit_l,CS.limit_l);
+        end
+        
+        
+        function time = getTime(CS)
+            time = 0;
+        end
+        
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.dot b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.dot
new file mode 100644
index 0000000..27819a1
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Windsorize -> Windsorize;
+
+  Windsorize [URL="Windsorize.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.html
new file mode 100644
index 0000000..f1c260b
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+preprocessing/@Windsorize</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@Windsorize">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Windsorize">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Windsorize</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Windsorize" border="2" style="color:#000;">  
+<map name="mainmap">
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+</map> 
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+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.map b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.map
new file mode 100644
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diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/index.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/index.html
new file mode 100644
index 0000000..c6b4343
--- /dev/null
+++ b/doc/+eegtoolkit/+preprocessing/@Windsorize/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+preprocessing/@Windsorize</title>
+  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@Windsorize">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Windsorize">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+preprocessing/@Windsorize</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Windsorize.html">Windsorize</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.html b/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.html
new file mode 100644
index 0000000..777c40c
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.html
@@ -0,0 +1,83 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of FusionInstanceSet</title>
+  <meta name="keywords" content="FusionInstanceSet">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@FusionInstanceSet</a> &gt; FusionInstanceSet.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@FusionInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>FusionInstanceSet
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FusionInstanceSet.html" class="code" title="">FusionInstanceSet</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="FusionInstanceSet.html" class="code" title="">FusionInstanceSet</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function FIS = FusionInstanceSet(baseInstanceSet)</a></li><li><a href="#_sub2" class="code">function FIS = addInstanceSet(FIS, instanceSet)</a></li><li><a href="#_sub3" class="code">function FIS = removeInstancesWithIndices(FIS, indices)</a></li><li><a href="#_sub4" class="code">function instances = getInstancesWithIndices(FIS, indices)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="FusionInstanceSet.m">FusionInstanceSet.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="FusionInstanceSet.html" class="code" title="">FusionInstanceSet</a> &lt; eegtoolkit.util.InstanceSet
+0002     properties
+0003         numFusion;
+0004         instanceSets;
+0005     <span class="keyword">end</span>
+0006     
+0007     methods 
+0008         <a name="_sub0" href="#_subfunctions" class="code">function FIS = FusionInstanceSet(baseInstanceSet)</a>
+0009             FIS = FIS@eegtoolkit.util.InstanceSet(baseInstanceSet.getDataset);
+0010             FIS.numFusion = 0;
+0011             FIS.instanceSets = {};
+0012         <span class="keyword">end</span>
+0013         
+0014         <a name="_sub1" href="#_subfunctions" class="code">function FIS = addInstanceSet(FIS, instanceSet)</a>
+0015             FIS.numFusion = FIS.numFusion + 1;
+0016             FIS.instanceSets{FIS.numFusion} = instanceSet;
+0017         <span class="keyword">end</span>
+0018         
+0019         <a name="_sub2" href="#_subfunctions" class="code">function FIS = removeInstancesWithIndices(FIS, indices)</a>
+0020             <span class="keyword">for</span> i=1:length(FIS.instanceSets)
+0021                 FIS.instanceSets{i} = FIS.instanceSets{i}.removeInstancesWithIndices(indices);
+0022             <span class="keyword">end</span>
+0023         <span class="keyword">end</span>
+0024         
+0025         <a name="_sub3" href="#_subfunctions" class="code">function instances = getInstancesWithIndices(FIS, indices)</a>
+0026             instances = zeros(length(indices),FIS.getNumFeatures,FIS.numFusion);
+0027             <span class="keyword">for</span> i=1:length(FIS.instanceSets)
+0028                 instances(:,:,i) = FIS.instanceSets{i}.getInstancesWithIndices(indices);
+0029             <span class="keyword">end</span>
+0030         <span class="keyword">end</span>
+0031     <span class="keyword">end</span>
+0032     
+0033 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.m b/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.m
new file mode 100644
index 0000000..f6cc0e0
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.m
@@ -0,0 +1,33 @@
+classdef FusionInstanceSet < eegtoolkit.util.InstanceSet
+    properties
+        numFusion;
+        instanceSets;
+    end
+    
+    methods 
+        function FIS = FusionInstanceSet(baseInstanceSet)
+            FIS = FIS@eegtoolkit.util.InstanceSet(baseInstanceSet.getDataset);
+            FIS.numFusion = 0;
+            FIS.instanceSets = {};
+        end
+        
+        function FIS = addInstanceSet(FIS, instanceSet)
+            FIS.numFusion = FIS.numFusion + 1;
+            FIS.instanceSets{FIS.numFusion} = instanceSet;
+        end
+        
+        function FIS = removeInstancesWithIndices(FIS, indices)
+            for i=1:length(FIS.instanceSets)
+                FIS.instanceSets{i} = FIS.instanceSets{i}.removeInstancesWithIndices(indices);
+            end
+        end
+        
+        function instances = getInstancesWithIndices(FIS, indices)
+            instances = zeros(length(indices),FIS.getNumFeatures,FIS.numFusion);
+            for i=1:length(FIS.instanceSets)
+                instances(:,:,i) = FIS.instanceSets{i}.getInstancesWithIndices(indices);
+            end
+        end
+    end
+    
+end
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.dot b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.dot
new file mode 100644
index 0000000..f8c92f9
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  FusionInstanceSet -> FusionInstanceSet;
+
+  FusionInstanceSet [URL="FusionInstanceSet.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.html b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.html
new file mode 100644
index 0000000..fed1895
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@FusionInstanceSet</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@FusionInstanceSet">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@FusionInstanceSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@FusionInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@FusionInstanceSet</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@FusionInstanceSet" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="FusionInstanceSet.html" title="FusionInstanceSet" alt="" coords="206,29,201,22,187,15,164,10,136,7,105,5,74,7,46,10,24,15,10,22,5,29,10,37,24,43,46,49,74,52,105,53,136,52,164,49,187,43,201,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.map b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.map
new file mode 100644
index 0000000..35af42a
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="FusionInstanceSet.html" title="FusionInstanceSet" alt="" coords="206,29,201,22,187,15,164,10,136,7,105,5,74,7,46,10,24,15,10,22,5,29,10,37,24,43,46,49,74,52,105,53,136,52,164,49,187,43,201,37">
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.png b/doc/+eegtoolkit/+util/@FusionInstanceSet/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/index.html b/doc/+eegtoolkit/+util/@FusionInstanceSet/index.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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+
+<h1>Index for ./+eegtoolkit/+util/@FusionInstanceSet</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="FusionInstanceSet.html">FusionInstanceSet</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+util/@InstanceSet/InstanceSet.html b/doc/+eegtoolkit/+util/@InstanceSet/InstanceSet.html
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--- /dev/null
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of InstanceSet</title>
+  <meta name="keywords" content="InstanceSet">
+  <meta name="description" content="A class for describing a set of instances and labels">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@InstanceSet</a> &gt; InstanceSet.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@InstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>InstanceSet
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>A class for describing a set of instances and labels</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> A class for describing a set of instances and labels
+ 
+ Properties:
+ -instances : a m x n matrix where m = # instances and n =
+ # features
+ -labels: a m x 1 matrix containing the labels for each
+ instance
+ -K: a m x m matrix containing the kernel of the instances
+ required only for the Fast vesrion of LibSVM
+
+ Functions:
+Construct an instanceSet
+   IS = eegtoolkit.util.InstanceSet(instances, labels)
+Compute the kernel
+   K = IS.computeKernel(kernel, gamma, maxlag, scaleopt)
+ kernel can be one of 'linear' (default),'rbf','chi','xcorr','spearman',
+ 'correlation','cosine','euclidean','seuclidean','mahalanobis'
+Get the training kernel with indexes in the trainidx vector
+   Ktrain = IS.getTrainKernel(trainidx)
+Get the test kernel with test indexes testidx and train indexes trainidx
+   Ktest = IS.getTestKernel(trainidx, testidx)
+Get instances of specific indices in vector idx
+   instance = IS.getInstancesWithIndices(idx)
+Get the instances of a specific label
+   instances = IS.getInstancesForLabel(label)
+Get the indices corresponding to a specific label
+   indices = IS.getInstanceIndicesForLabel(label)
+Get the instances including the labels as the last row
+   dataset = getDataset(IS)
+Get the instances with specific indices. The last column of the matrix 
+will contain the label.
+   dataset = IS.getDatasetWithIndices(idx)
+Remove instances with specific indices. A new InstanceSet object is 
+returned by this function without the specified instances
+   IS = IS.removeInstancesWithIndices(idx)
+ Write the dataset to a csv file
+   IS.writeCSV(csvname)
+Write the dataset to a weka-readable file (arff). The whole dataset is
+written if the indices are not given (function called with 1 argument)
+   IS.writeArff(fname, indices)</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="InstanceSet.html" class="code" title="">InstanceSet</a>	A class for describing a set of instances and labels</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="InstanceSet.html" class="code" title="">InstanceSet</a>	A class for describing a set of instances and labels</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function IS = InstanceSet(instances, labels)</a></li><li><a href="#_sub2" class="code">function instances = getInstances(IS)</a></li><li><a href="#_sub3" class="code">function K = computeKernel(IS,kernel, gamma, maxlag, scaleopt)</a></li><li><a href="#_sub4" class="code">function Ktrain = getTrainKernel(IS, trainidx)</a></li><li><a href="#_sub5" class="code">function Ktest = getTestKernel(IS, trainidx, testidx)</a></li><li><a href="#_sub6" class="code">function instance = getInstancesWithIndices(IS, idx)</a></li><li><a href="#_sub7" class="code">function labels = getLabels(IS)</a></li><li><a href="#_sub8" class="code">function numLabels = getNumLabels(IS)</a></li><li><a href="#_sub9" class="code">function numInstances = getNumInstances(IS)</a></li><li><a href="#_sub10" class="code">function numFeatures = getNumFeatures(IS)</a></li><li><a href="#_sub11" class="code">function instances = getInstancesForLabel(IS, label)</a></li><li><a href="#_sub12" class="code">function indices = getInstanceIndicesForLabel(IS,label)</a></li><li><a href="#_sub13" class="code">function dataset = getDataset(IS)</a></li><li><a href="#_sub14" class="code">function dataset = getDatasetWithIndices(IS,idx)</a></li><li><a href="#_sub15" class="code">function IS = removeInstancesWithIndices(IS, idx)</a></li><li><a href="#_sub16" class="code">function writeCSV(IS, csvname)</a></li><li><a href="#_sub17" class="code">function writeArff(IS, fname, indices)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="InstanceSet.m">InstanceSet.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% A class for describing a set of instances and labels</span>
+0002 <span class="comment">%</span>
+0003 <span class="comment">% Properties:</span>
+0004 <span class="comment">% -instances : a m x n matrix where m = # instances and n =</span>
+0005 <span class="comment">% # features</span>
+0006 <span class="comment">% -labels: a m x 1 matrix containing the labels for each</span>
+0007 <span class="comment">% instance</span>
+0008 <span class="comment">% -K: a m x m matrix containing the kernel of the instances</span>
+0009 <span class="comment">% required only for the Fast vesrion of LibSVM</span>
+0010 <span class="comment">%</span>
+0011 <span class="comment">% Functions:</span>
+0012 <span class="comment">%Construct an instanceSet</span>
+0013 <span class="comment">%   IS = eegtoolkit.util.InstanceSet(instances, labels)</span>
+0014 <span class="comment">%Compute the kernel</span>
+0015 <span class="comment">%   K = IS.computeKernel(kernel, gamma, maxlag, scaleopt)</span>
+0016 <span class="comment">% kernel can be one of 'linear' (default),'rbf','chi','xcorr','spearman',</span>
+0017 <span class="comment">% 'correlation','cosine','euclidean','seuclidean','mahalanobis'</span>
+0018 <span class="comment">%Get the training kernel with indexes in the trainidx vector</span>
+0019 <span class="comment">%   Ktrain = IS.getTrainKernel(trainidx)</span>
+0020 <span class="comment">%Get the test kernel with test indexes testidx and train indexes trainidx</span>
+0021 <span class="comment">%   Ktest = IS.getTestKernel(trainidx, testidx)</span>
+0022 <span class="comment">%Get instances of specific indices in vector idx</span>
+0023 <span class="comment">%   instance = IS.getInstancesWithIndices(idx)</span>
+0024 <span class="comment">%Get the instances of a specific label</span>
+0025 <span class="comment">%   instances = IS.getInstancesForLabel(label)</span>
+0026 <span class="comment">%Get the indices corresponding to a specific label</span>
+0027 <span class="comment">%   indices = IS.getInstanceIndicesForLabel(label)</span>
+0028 <span class="comment">%Get the instances including the labels as the last row</span>
+0029 <span class="comment">%   dataset = getDataset(IS)</span>
+0030 <span class="comment">%Get the instances with specific indices. The last column of the matrix</span>
+0031 <span class="comment">%will contain the label.</span>
+0032 <span class="comment">%   dataset = IS.getDatasetWithIndices(idx)</span>
+0033 <span class="comment">%Remove instances with specific indices. A new InstanceSet object is</span>
+0034 <span class="comment">%returned by this function without the specified instances</span>
+0035 <span class="comment">%   IS = IS.removeInstancesWithIndices(idx)</span>
+0036 <span class="comment">% Write the dataset to a csv file</span>
+0037 <span class="comment">%   IS.writeCSV(csvname)</span>
+0038 <span class="comment">%Write the dataset to a weka-readable file (arff). The whole dataset is</span>
+0039 <span class="comment">%written if the indices are not given (function called with 1 argument)</span>
+0040 <span class="comment">%   IS.writeArff(fname, indices)</span>
+0041 
+0042 classdef <a href="InstanceSet.html" class="code" title="">InstanceSet</a>
+0043     properties (Access = public)
+0044         instances; <span class="comment">% the instances</span>
+0045         labels; <span class="comment">% the labels</span>
+0046         K; <span class="comment">% the kernel of the instances</span>
+0047     <span class="keyword">end</span>
+0048     
+0049     methods
+0050         <a name="_sub0" href="#_subfunctions" class="code">function IS = InstanceSet(instances, labels)</a>
+0051             <span class="comment">% obj = InstanceSet(instances, labels)</span>
+0052             
+0053             <span class="keyword">if</span> nargin == 1
+0054                 [~, cols] = size(instances);
+0055                 IS.instances = instances(:,1:cols-1);
+0056                 IS.labels = instances(:,cols);
+0057             <span class="keyword">elseif</span> nargin==2
+0058                 IS.instances = instances;
+0059                 IS.labels = floor(labels);
+0060             <span class="keyword">end</span>
+0061             <span class="comment">%             for i=1:size(IS.instances,1)</span>
+0062             <span class="comment">%                 IS.instances(i,:) = IS.instances(i,:)./norm(IS.instances(i,:));</span>
+0063             <span class="comment">%             end</span>
+0064         <span class="keyword">end</span>
+0065         
+0066         <a name="_sub1" href="#_subfunctions" class="code">function instances = getInstances(IS)</a>
+0067             <span class="comment">% get the instances</span>
+0068             instances = IS.instances;
+0069         <span class="keyword">end</span>
+0070         
+0071         <a name="_sub2" href="#_subfunctions" class="code">function K = computeKernel(IS,kernel, gamma, maxlag, scaleopt)</a>
+0072             <span class="keyword">switch</span> kernel
+0073                 <span class="keyword">case</span> <span class="string">'linear'</span>
+0074                     K = IS.instances*IS.instances';
+0075                 <span class="keyword">case</span> <span class="string">'rbf'</span>
+0076                     dist = pdist2(IS.instances,IS.instances).^2;
+0077                     <span class="comment">%                     N = size(IS.instances,1);</span>
+0078                     <span class="comment">%                     dist = repmat(sum(IS.instances.^2, 2)', [N 1])' + ...</span>
+0079                     <span class="comment">%                         repmat(sum(IS.instances.^2,2)', [N 1]) - ...</span>
+0080                     <span class="comment">%                         2.*IS.instances*IS.instances';</span>
+0081                     K = exp(-gamma.*dist);
+0082                 <span class="keyword">case</span> <span class="string">'chi'</span>
+0083                     m = size(IS.instances,1);
+0084                     n = size(IS.instances,1);
+0085                     mOnes = ones(1,m); D = zeros(m,n);
+0086                     <span class="keyword">for</span> i=1:n
+0087                         yi = IS.instances(i,:);  yiRep = yi( mOnes, : );
+0088                         s = yiRep + IS.instances;    d = yiRep - IS.instances;
+0089                         D(:,i) = sum( d.^2 ./ (s+eps), 2 );
+0090                     <span class="keyword">end</span>
+0091                     D = D/2;
+0092                     K = exp(-gamma.*D);
+0093                     <span class="comment">%                     error('chi kernel not implemented yet');</span>
+0094                 <span class="keyword">case</span> <span class="string">'xcorr'</span>
+0095                     K = zeros(size(IS.instances,1));
+0096                     <span class="keyword">if</span> size(IS.instances,2) &lt; 500 <span class="comment">% if memory allows it go for the vectorized version</span>
+0097                         a = xcorr(IS.instances',maxlag,scaleopt);
+0098                         c = reshape(a, 2*maxlag+1, size(IS.instances,1), size(IS.instances,1));
+0099                         <span class="keyword">if</span> size(c,1) == 1 <span class="comment">% no max is required</span>
+0100                             K = squeeze(c);
+0101                         <span class="keyword">else</span>
+0102                             K = squeeze(max(c));
+0103                         <span class="keyword">end</span>
+0104                     <span class="keyword">else</span>
+0105                         <span class="keyword">for</span> i=1:size(IS.instances,1)
+0106                             <span class="keyword">for</span> j=i:size(IS.instances,1)
+0107                                 K(i,j)=max(xcorr(IS.instances(i,:),IS.instances(j,:),maxlag,scaleopt));
+0108                                 K(j,i)=K(i,j);
+0109                             <span class="keyword">end</span>
+0110                         <span class="keyword">end</span>
+0111                     <span class="keyword">end</span>
+0112                 <span class="keyword">case</span> {<span class="string">'spearman'</span>,<span class="string">'correlation'</span>,<span class="string">'cosine'</span>}
+0113                     dist = pdist2(IS.instances,IS.instances,kernel);
+0114                     K = 1-dist;
+0115                 <span class="keyword">case</span> {<span class="string">'euclidean'</span>,<span class="string">'seuclidean'</span>,<span class="string">'mahalanobis'</span>}
+0116                     dist = pdist2(IS.instances,IS.instances,kernel).^2;
+0117                     K = exp(-gamma.*dist);
+0118                 <span class="keyword">otherwise</span> <span class="comment">% if not one of the above, it can either be any value of distance in pdist2 or a function handle</span>
+0119                     dist = pdist2(IS.instances,IS.instances,kernel);
+0120                     K = exp(-gamma.*dist);
+0121             <span class="keyword">end</span>
+0122         <span class="keyword">end</span>
+0123         
+0124         <a name="_sub3" href="#_subfunctions" class="code">function Ktrain = getTrainKernel(IS, trainidx)</a>
+0125             Ktrain = IS.K(trainidx,trainidx);
+0126         <span class="keyword">end</span>
+0127         
+0128         <a name="_sub4" href="#_subfunctions" class="code">function Ktest = getTestKernel(IS, trainidx, testidx)</a>
+0129             Ktest = IS.K(testidx,trainidx);
+0130         <span class="keyword">end</span>
+0131         
+0132         <a name="_sub5" href="#_subfunctions" class="code">function instance = getInstancesWithIndices(IS, idx)</a>
+0133             <span class="comment">% get instances of specific indices</span>
+0134             instance = IS.instances(idx,:);
+0135         <span class="keyword">end</span>
+0136         <a name="_sub6" href="#_subfunctions" class="code">function labels = getLabels(IS)</a>
+0137             <span class="comment">% get the labels</span>
+0138             labels = IS.labels;
+0139         <span class="keyword">end</span>
+0140         
+0141         <a name="_sub7" href="#_subfunctions" class="code">function numLabels = getNumLabels(IS)</a>
+0142             <span class="comment">% get the number of labels</span>
+0143             numLabels = length(unique(IS.getLabels()));
+0144         <span class="keyword">end</span>
+0145         
+0146         <a name="_sub8" href="#_subfunctions" class="code">function numInstances = getNumInstances(IS)</a>
+0147             <span class="comment">% get the number of instances</span>
+0148             [numInstances,~] = size(IS.instances);
+0149         <span class="keyword">end</span>
+0150         
+0151         <a name="_sub9" href="#_subfunctions" class="code">function numFeatures = getNumFeatures(IS)</a>
+0152             <span class="comment">% get the number of features</span>
+0153             [~, numFeatures] = size(IS.instances);
+0154         <span class="keyword">end</span>
+0155         
+0156         
+0157         <a name="_sub10" href="#_subfunctions" class="code">function instances = getInstancesForLabel(IS, label)</a>
+0158             <span class="comment">% get the instances of a specific label</span>
+0159             indices = IS.getInstanceIndicesForLabel(label);
+0160             instances = IS.getInstances();
+0161             instances = instances(indices,:);
+0162         <span class="keyword">end</span>
+0163         
+0164         <a name="_sub11" href="#_subfunctions" class="code">function indices = getInstanceIndicesForLabel(IS,label)</a>
+0165             <span class="comment">% get the indices corresponding to a specific label</span>
+0166             [indices, ~] = find(IS.getDataset()==label);
+0167         <span class="keyword">end</span>
+0168         
+0169         <a name="_sub12" href="#_subfunctions" class="code">function dataset = getDataset(IS)</a>
+0170             <span class="comment">% same with getInstances but includes the labels as the last</span>
+0171             <span class="comment">% row</span>
+0172             dataset = horzcat(IS.instances,IS.labels);
+0173         <span class="keyword">end</span>
+0174         
+0175         <a name="_sub13" href="#_subfunctions" class="code">function dataset = getDatasetWithIndices(IS,idx)</a>
+0176             <span class="comment">% get the instances with specific indices. The last column of</span>
+0177             <span class="comment">% the matrix will contain the label.</span>
+0178             instance = IS.instances(idx,:);
+0179             label = IS.labels(idx,:);
+0180             dataset = horzcat(instance,label);
+0181         <span class="keyword">end</span>
+0182         <a name="_sub14" href="#_subfunctions" class="code">function IS = removeInstancesWithIndices(IS, idx)</a>
+0183             <span class="comment">% remove instances with specific indices. A new InstanceSet</span>
+0184             <span class="comment">% object is returned by this functioned without the specified</span>
+0185             <span class="comment">% instances</span>
+0186             IS.instances(idx,:) = [];
+0187             IS.labels(idx,:) = [];
+0188         <span class="keyword">end</span>
+0189         <a name="_sub15" href="#_subfunctions" class="code">function writeCSV(IS, csvname)</a>
+0190             <span class="comment">% write the dataset to a csv file</span>
+0191             <span class="comment">% Example:</span>
+0192             <span class="comment">%   obj.writeCSV('data.csv');</span>
+0193             csvwrite(csvname, IS.getDataset());
+0194         <span class="keyword">end</span>
+0195         <a name="_sub16" href="#_subfunctions" class="code">function writeArff(IS, fname, indices)</a>
+0196             <span class="comment">% write the dataset to a weka-readable file (arff)</span>
+0197             <span class="comment">% Caution: filename without extension</span>
+0198             <span class="comment">% Example:</span>
+0199             <span class="comment">%   obj.writeArff('data')</span>
+0200             <span class="keyword">if</span> nargin==3
+0201                 data1 = IS.getDatasetWithIndices(indices);
+0202                 is1 = eegtoolkit.util.InstanceSet(data1);
+0203                 data2 = IS.getDatasetWithIndices(~indices);
+0204                 is2 = eegtoolkit.util.InstanceSet(data2);
+0205                 is1.writeArff(sprintf(<span class="string">'test%s'</span>, fname));
+0206                 is2.writeArff(sprintf(<span class="string">'train%s'</span>,fname));
+0207                 <span class="keyword">return</span>;
+0208             <span class="keyword">else</span>
+0209                 data = IS.getDataset();
+0210             <span class="keyword">end</span>
+0211             <span class="comment">%             data = horzcat(IS.instances,floor(IS.labels));</span>
+0212             sss=size(data,2)-1;
+0213             filename1=strcat(fname,<span class="string">'.arff'</span>);
+0214             out1 = fopen (filename1, <span class="string">'w+'</span>);
+0215             aa1=strcat(<span class="string">'@relation'</span>,{<span class="string">' '</span>},fname,<span class="string">'-weka.filters.unsupervised.attribute.NumericToNominal-Rlast'</span>);
+0216             fprintf (out1, <span class="string">'%s\n'</span>, char(aa1));
+0217             <span class="keyword">for</span> jj=1:sss
+0218                 fprintf (out1, <span class="string">'@attribute %s numeric\n'</span>,num2str(jj));
+0219             <span class="keyword">end</span>
+0220             n_classes=max(unique(data(:,end)));
+0221             txt1=strcat(<span class="string">'@attribute'</span>,{<span class="string">' '</span>},num2str(sss+1),{<span class="string">' {'</span>});
+0222             
+0223             <span class="keyword">for</span> ii=1:n_classes
+0224                 txt1=strcat(txt1,num2str(ii),{<span class="string">','</span>});
+0225             <span class="keyword">end</span>
+0226             txt1=strcat(txt1,{<span class="string">'}'</span>});
+0227             
+0228             fprintf (out1, <span class="string">'%s\n\n'</span>,char(txt1));
+0229             fprintf (out1,<span class="string">'@data\n'</span>);
+0230             
+0231             fclose(out1);
+0232             
+0233             dlmwrite (filename1, data, <span class="string">'-append'</span> );
+0234         <span class="keyword">end</span>
+0235     <span class="keyword">end</span>
+0236     
+0237 <span class="keyword">end</span>
+0238</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@InstanceSet/InstanceSet.m b/doc/+eegtoolkit/+util/@InstanceSet/InstanceSet.m
new file mode 100644
index 0000000..fbe2fc4
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@InstanceSet/InstanceSet.m
@@ -0,0 +1,238 @@
+% A class for describing a set of instances and labels
+% 
+% Properties:
+% -instances : a m x n matrix where m = # instances and n =
+% # features
+% -labels: a m x 1 matrix containing the labels for each
+% instance
+% -K: a m x m matrix containing the kernel of the instances
+% required only for the Fast vesrion of LibSVM
+%
+% Functions:
+%Construct an instanceSet
+%   IS = eegtoolkit.util.InstanceSet(instances, labels)
+%Compute the kernel
+%   K = IS.computeKernel(kernel, gamma, maxlag, scaleopt)
+% kernel can be one of 'linear' (default),'rbf','chi','xcorr','spearman',
+% 'correlation','cosine','euclidean','seuclidean','mahalanobis'
+%Get the training kernel with indexes in the trainidx vector
+%   Ktrain = IS.getTrainKernel(trainidx)
+%Get the test kernel with test indexes testidx and train indexes trainidx
+%   Ktest = IS.getTestKernel(trainidx, testidx)
+%Get instances of specific indices in vector idx
+%   instance = IS.getInstancesWithIndices(idx)
+%Get the instances of a specific label
+%   instances = IS.getInstancesForLabel(label)
+%Get the indices corresponding to a specific label
+%   indices = IS.getInstanceIndicesForLabel(label)
+%Get the instances including the labels as the last row
+%   dataset = getDataset(IS)
+%Get the instances with specific indices. The last column of the matrix 
+%will contain the label.
+%   dataset = IS.getDatasetWithIndices(idx)
+%Remove instances with specific indices. A new InstanceSet object is 
+%returned by this function without the specified instances
+%   IS = IS.removeInstancesWithIndices(idx)
+% Write the dataset to a csv file
+%   IS.writeCSV(csvname)
+%Write the dataset to a weka-readable file (arff). The whole dataset is
+%written if the indices are not given (function called with 1 argument)
+%   IS.writeArff(fname, indices)
+
+classdef InstanceSet
+    properties (Access = public)
+        instances; % the instances
+        labels; % the labels
+        K; % the kernel of the instances
+    end
+    
+    methods
+        function IS = InstanceSet(instances, labels)
+            % obj = InstanceSet(instances, labels)
+            
+            if nargin == 1
+                [~, cols] = size(instances);
+                IS.instances = instances(:,1:cols-1);
+                IS.labels = instances(:,cols);
+            elseif nargin==2
+                IS.instances = instances;
+                IS.labels = floor(labels);
+            end
+            %             for i=1:size(IS.instances,1)
+            %                 IS.instances(i,:) = IS.instances(i,:)./norm(IS.instances(i,:));
+            %             end
+        end
+        
+        function instances = getInstances(IS)
+            % get the instances
+            instances = IS.instances;
+        end
+        
+        function K = computeKernel(IS,kernel, gamma, maxlag, scaleopt)
+            switch kernel
+                case 'linear'
+                    K = IS.instances*IS.instances';
+                case 'rbf'
+                    dist = pdist2(IS.instances,IS.instances).^2;
+                    %                     N = size(IS.instances,1);
+                    %                     dist = repmat(sum(IS.instances.^2, 2)', [N 1])' + ...
+                    %                         repmat(sum(IS.instances.^2,2)', [N 1]) - ...
+                    %                         2.*IS.instances*IS.instances';
+                    K = exp(-gamma.*dist);
+                case 'chi'
+                    m = size(IS.instances,1);
+                    n = size(IS.instances,1);
+                    mOnes = ones(1,m); D = zeros(m,n);
+                    for i=1:n
+                        yi = IS.instances(i,:);  yiRep = yi( mOnes, : );
+                        s = yiRep + IS.instances;    d = yiRep - IS.instances;
+                        D(:,i) = sum( d.^2 ./ (s+eps), 2 );
+                    end
+                    D = D/2;
+                    K = exp(-gamma.*D);
+                    %                     error('chi kernel not implemented yet');
+                case 'xcorr'
+                    K = zeros(size(IS.instances,1));
+                    if size(IS.instances,2) < 500 % if memory allows it go for the vectorized version
+                        a = xcorr(IS.instances',maxlag,scaleopt);
+                        c = reshape(a, 2*maxlag+1, size(IS.instances,1), size(IS.instances,1));
+                        if size(c,1) == 1 % no max is required
+                            K = squeeze(c);
+                        else
+                            K = squeeze(max(c));
+                        end
+                    else
+                        for i=1:size(IS.instances,1)
+                            for j=i:size(IS.instances,1)
+                                K(i,j)=max(xcorr(IS.instances(i,:),IS.instances(j,:),maxlag,scaleopt));
+                                K(j,i)=K(i,j);
+                            end
+                        end
+                    end
+                case {'spearman','correlation','cosine'}
+                    dist = pdist2(IS.instances,IS.instances,kernel);
+                    K = 1-dist;
+                case {'euclidean','seuclidean','mahalanobis'}
+                    dist = pdist2(IS.instances,IS.instances,kernel).^2;
+                    K = exp(-gamma.*dist);
+                otherwise % if not one of the above, it can either be any value of distance in pdist2 or a function handle
+                    dist = pdist2(IS.instances,IS.instances,kernel);
+                    K = exp(-gamma.*dist);
+            end
+        end
+        
+        function Ktrain = getTrainKernel(IS, trainidx)
+            Ktrain = IS.K(trainidx,trainidx);
+        end
+        
+        function Ktest = getTestKernel(IS, trainidx, testidx)
+            Ktest = IS.K(testidx,trainidx);
+        end
+        
+        function instance = getInstancesWithIndices(IS, idx)
+            % get instances of specific indices
+            instance = IS.instances(idx,:);
+        end
+        function labels = getLabels(IS)
+            % get the labels
+            labels = IS.labels;
+        end
+        
+        function numLabels = getNumLabels(IS)
+            % get the number of labels
+            numLabels = length(unique(IS.getLabels()));
+        end
+        
+        function numInstances = getNumInstances(IS)
+            % get the number of instances
+            [numInstances,~] = size(IS.instances);
+        end
+        
+        function numFeatures = getNumFeatures(IS)
+            % get the number of features
+            [~, numFeatures] = size(IS.instances);
+        end
+        
+        
+        function instances = getInstancesForLabel(IS, label)
+            % get the instances of a specific label
+            indices = IS.getInstanceIndicesForLabel(label);
+            instances = IS.getInstances();
+            instances = instances(indices,:);
+        end
+        
+        function indices = getInstanceIndicesForLabel(IS,label)
+            % get the indices corresponding to a specific label
+            [indices, ~] = find(IS.getDataset()==label);
+        end
+        
+        function dataset = getDataset(IS)
+            % same with getInstances but includes the labels as the last
+            % row
+            dataset = horzcat(IS.instances,IS.labels);
+        end
+        
+        function dataset = getDatasetWithIndices(IS,idx)
+            % get the instances with specific indices. The last column of
+            % the matrix will contain the label.
+            instance = IS.instances(idx,:);
+            label = IS.labels(idx,:);
+            dataset = horzcat(instance,label);
+        end
+        function IS = removeInstancesWithIndices(IS, idx)
+            % remove instances with specific indices. A new InstanceSet
+            % object is returned by this functioned without the specified
+            % instances
+            IS.instances(idx,:) = [];
+            IS.labels(idx,:) = [];
+        end
+        function writeCSV(IS, csvname)
+            % write the dataset to a csv file
+            % Example:
+            %   obj.writeCSV('data.csv');
+            csvwrite(csvname, IS.getDataset());
+        end
+        function writeArff(IS, fname, indices)
+            % write the dataset to a weka-readable file (arff)
+            % Caution: filename without extension
+            % Example:
+            %   obj.writeArff('data')
+            if nargin==3
+                data1 = IS.getDatasetWithIndices(indices);
+                is1 = eegtoolkit.util.InstanceSet(data1);
+                data2 = IS.getDatasetWithIndices(~indices);
+                is2 = eegtoolkit.util.InstanceSet(data2);
+                is1.writeArff(sprintf('test%s', fname));
+                is2.writeArff(sprintf('train%s',fname));
+                return;
+            else
+                data = IS.getDataset();
+            end
+            %             data = horzcat(IS.instances,floor(IS.labels));
+            sss=size(data,2)-1;
+            filename1=strcat(fname,'.arff');
+            out1 = fopen (filename1, 'w+');
+            aa1=strcat('@relation',{' '},fname,'-weka.filters.unsupervised.attribute.NumericToNominal-Rlast');
+            fprintf (out1, '%s\n', char(aa1));
+            for jj=1:sss
+                fprintf (out1, '@attribute %s numeric\n',num2str(jj));
+            end
+            n_classes=max(unique(data(:,end)));
+            txt1=strcat('@attribute',{' '},num2str(sss+1),{' {'});
+            
+            for ii=1:n_classes
+                txt1=strcat(txt1,num2str(ii),{','});
+            end
+            txt1=strcat(txt1,{'}'});
+            
+            fprintf (out1, '%s\n\n',char(txt1));
+            fprintf (out1,'@data\n');
+            
+            fclose(out1);
+            
+            dlmwrite (filename1, data, '-append' );
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+util/@InstanceSet/graph.dot b/doc/+eegtoolkit/+util/@InstanceSet/graph.dot
new file mode 100644
index 0000000..4199c12
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@InstanceSet/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  InstanceSet -> InstanceSet;
+
+  InstanceSet [URL="InstanceSet.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@InstanceSet/graph.html b/doc/+eegtoolkit/+util/@InstanceSet/graph.html
new file mode 100644
index 0000000..61ce11e
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@InstanceSet/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@InstanceSet</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@InstanceSet">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@InstanceSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@InstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@InstanceSet</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@InstanceSet" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="InstanceSet.html" title="InstanceSet" alt="" coords="142,29,138,22,129,15,114,10,94,7,73,5,52,7,33,10,18,15,8,22,5,29,8,37,18,43,33,49,52,52,73,53,94,52,114,49,129,43,138,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@InstanceSet/graph.map b/doc/+eegtoolkit/+util/@InstanceSet/graph.map
new file mode 100644
index 0000000..9544beb
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@InstanceSet/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="InstanceSet.html" title="InstanceSet" alt="" coords="142,29,138,22,129,15,114,10,94,7,73,5,52,7,33,10,18,15,8,22,5,29,8,37,18,43,33,49,52,52,73,53,94,52,114,49,129,43,138,37">
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new file mode 100644
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diff --git a/doc/+eegtoolkit/+util/@InstanceSet/index.html b/doc/+eegtoolkit/+util/@InstanceSet/index.html
new file mode 100644
index 0000000..903c4ed
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@InstanceSet/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@InstanceSet</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@InstanceSet">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@InstanceSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@InstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@InstanceSet</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="InstanceSet.html">InstanceSet</a></td><td>A class for describing a set of instances and labels </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.html b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.html
new file mode 100644
index 0000000..aca3de6
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.html
@@ -0,0 +1,125 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of L1MCCAInstanceSet</title>
+  <meta name="keywords" content="L1MCCAInstanceSet">
+  <meta name="description" content="RESULTSET class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@L1MCCAInstanceSet</a> &gt; L1MCCAInstanceSet.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>L1MCCAInstanceSet
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>RESULTSET class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> RESULTSET class
+ Stores the results of an experiment</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="L1MCCAInstanceSet.html" class="code" title="">L1MCCAInstanceSet</a>	RESULTSET class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="L1MCCAInstanceSet.html" class="code" title="">L1MCCAInstanceSet</a>	RESULTSET class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function L1 = L1MCCAInstanceSet(trials)</a></li><li><a href="#_sub2" class="code">function newL1 = removeInstancesWithIndices(L1,indices)</a></li><li><a href="#_sub3" class="code">function instances = getInstancesWithIndices(L1,indices)</a></li><li><a href="#_sub4" class="code">function dataset = getDatasetWithIndices(L1,indices)</a></li><li><a href="#_sub5" class="code">function numInstances = getNumInstances(L1)</a></li><li><a href="#_sub6" class="code">function dataset = getDataset(L1)</a></li><li><a href="#_sub7" class="code">function numLabels = getNumLabels(L1)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="L1MCCAInstanceSet.m">L1MCCAInstanceSet.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% RESULTSET class</span>
+0002 <span class="comment">% Stores the results of an experiment</span>
+0003 classdef <a href="L1MCCAInstanceSet.html" class="code" title="">L1MCCAInstanceSet</a> &lt; eegtoolkit.util.InstanceSet
+0004     
+0005     properties
+0006         matrix4D;
+0007         labelss;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods
+0011         <a name="_sub0" href="#_subfunctions" class="code">function L1 = L1MCCAInstanceSet(trials)</a>
+0012             <span class="comment">%Constructor method</span>
+0013             <span class="comment">%Input:</span>
+0014             <span class="comment">%(InstanceSet object): the original instanceSet</span>
+0015             <span class="comment">%Labels: a vector containing the output labels of the</span>
+0016             <span class="comment">%experiment</span>
+0017             <span class="comment">%Proababilities: a vector containing the probabilities of each</span>
+0018             <span class="comment">%label</span>
+0019             <span class="comment">%Ranking (optional): a matrix containing a score for each label</span>
+0020             L1 = L1@eegtoolkit.util.InstanceSet(zeros(1,1000),ones(1,1000));
+0021             <span class="keyword">if</span>(nargin&gt;0)
+0022                 numTrials = length(trials);
+0023                 lbls = zeros(numTrials,1);
+0024                 <span class="keyword">for</span> i=1:numTrials
+0025                     lbls(i) = trials{i}.label;
+0026                 <span class="keyword">end</span>
+0027 
+0028                 L1.labelss = lbls;
+0029                 [numChannels, numSamples] = size(trials{1}.signal);
+0030                 
+0031                 L1.matrix4D = zeros(numChannels,numSamples,numTrials,1);
+0032                 
+0033                 <span class="keyword">for</span> i=1:numTrials
+0034                     L1.matrix4D(:,:,i) = trials{i}.signal;
+0035                 <span class="keyword">end</span>
+0036             <span class="keyword">end</span>
+0037 
+0038         <span class="keyword">end</span>
+0039         
+0040         <a name="_sub1" href="#_subfunctions" class="code">function newL1 = removeInstancesWithIndices(L1,indices)</a>
+0041             newL1 = eegtoolkit.util.L1MCCAInstanceSet;
+0042             newL1.labelss = L1.labelss;
+0043             newL1.labelss(indices) = [];
+0044             newL1.matrix4D = L1.matrix4D;
+0045             newL1.matrix4D(:,:,indices) = [];
+0046         <span class="keyword">end</span>
+0047         
+0048         <a name="_sub2" href="#_subfunctions" class="code">function instances = getInstancesWithIndices(L1,indices)</a>
+0049             instances = L1.matrix4D(:,:,indices);
+0050         <span class="keyword">end</span>
+0051         
+0052         <a name="_sub3" href="#_subfunctions" class="code">function dataset = getDatasetWithIndices(L1,indices)</a>
+0053             instances = zeros(length(indices),1000);
+0054             labels = L1.labelss(indices);
+0055             dataset = horzcat(instances,labels);
+0056         <span class="keyword">end</span>
+0057         
+0058         <a name="_sub4" href="#_subfunctions" class="code">function numInstances = getNumInstances(L1)</a>
+0059             [~,~,numInstances] = size(L1.matrix4D);
+0060         <span class="keyword">end</span>
+0061         
+0062         <a name="_sub5" href="#_subfunctions" class="code">function dataset = getDataset(L1)</a>
+0063             instances = zeros(L1.getNumInstances,1000);
+0064             labels = L1.labelss;
+0065             dataset = horzcat(instances,labels);
+0066         <span class="keyword">end</span>
+0067             
+0068         <a name="_sub6" href="#_subfunctions" class="code">function numLabels = getNumLabels(L1)</a>
+0069             numLabels = length(unique(L1.labelss));
+0070         <span class="keyword">end</span>
+0071     <span class="keyword">end</span>
+0072     
+0073 <span class="keyword">end</span>
+0074</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.m b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.m
new file mode 100644
index 0000000..bda3877
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/L1MCCAInstanceSet.m
@@ -0,0 +1,74 @@
+% RESULTSET class
+% Stores the results of an experiment
+classdef L1MCCAInstanceSet < eegtoolkit.util.InstanceSet
+    
+    properties
+        matrix4D;
+        labelss;
+    end
+    
+    methods
+        function L1 = L1MCCAInstanceSet(trials)
+            %Constructor method
+            %Input:
+            %(InstanceSet object): the original instanceSet
+            %Labels: a vector containing the output labels of the
+            %experiment
+            %Proababilities: a vector containing the probabilities of each
+            %label
+            %Ranking (optional): a matrix containing a score for each label
+            L1 = L1@eegtoolkit.util.InstanceSet(zeros(1,1000),ones(1,1000));
+            if(nargin>0)
+                numTrials = length(trials);
+                lbls = zeros(numTrials,1);
+                for i=1:numTrials
+                    lbls(i) = trials{i}.label;
+                end
+
+                L1.labelss = lbls;
+                [numChannels, numSamples] = size(trials{1}.signal);
+                
+                L1.matrix4D = zeros(numChannels,numSamples,numTrials,1);
+                
+                for i=1:numTrials
+                    L1.matrix4D(:,:,i) = trials{i}.signal;
+                end
+            end
+
+        end
+        
+        function newL1 = removeInstancesWithIndices(L1,indices)
+            newL1 = eegtoolkit.util.L1MCCAInstanceSet;
+            newL1.labelss = L1.labelss;
+            newL1.labelss(indices) = [];
+            newL1.matrix4D = L1.matrix4D;
+            newL1.matrix4D(:,:,indices) = [];
+        end
+        
+        function instances = getInstancesWithIndices(L1,indices)
+            instances = L1.matrix4D(:,:,indices);
+        end
+        
+        function dataset = getDatasetWithIndices(L1,indices)
+            instances = zeros(length(indices),1000);
+            labels = L1.labelss(indices);
+            dataset = horzcat(instances,labels);
+        end
+        
+        function numInstances = getNumInstances(L1)
+            [~,~,numInstances] = size(L1.matrix4D);
+        end
+        
+        function dataset = getDataset(L1)
+            instances = zeros(L1.getNumInstances,1000);
+            labels = L1.labelss;
+            dataset = horzcat(instances,labels);
+        end
+            
+        function numLabels = getNumLabels(L1)
+            numLabels = length(unique(L1.labelss));
+        end
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.dot b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.dot
new file mode 100644
index 0000000..0498a3e
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  L1MCCAInstanceSet -> L1MCCAInstanceSet;
+
+  L1MCCAInstanceSet [URL="L1MCCAInstanceSet.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.html b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.html
new file mode 100644
index 0000000..fd2a3f3
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@L1MCCAInstanceSet</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@L1MCCAInstanceSet">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@L1MCCAInstanceSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@L1MCCAInstanceSet</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@L1MCCAInstanceSet" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="L1MCCAInstanceSet.html" title="L1MCCAInstanceSet" alt="" coords="237,29,232,22,215,15,190,10,157,7,121,5,85,7,53,10,27,15,11,22,5,29,11,37,27,43,53,49,85,52,121,53,157,52,190,49,215,43,232,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.map b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/graph.map
new file mode 100644
index 0000000..69774f9
--- /dev/null
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diff --git a/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/index.html b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/index.html
new file mode 100644
index 0000000..ee82013
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@L1MCCAInstanceSet/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@L1MCCAInstanceSet</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@L1MCCAInstanceSet">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@L1MCCAInstanceSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="L1MCCAInstanceSet.html">L1MCCAInstanceSet</a></td><td>RESULTSET class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.html b/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.html
new file mode 100644
index 0000000..dc45675
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.html
@@ -0,0 +1,310 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of LSLWrapper</title>
+  <meta name="keywords" content="LSLWrapper">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@LSLWrapper</a> &gt; LSLWrapper.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@LSLWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>LSLWrapper
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LSLWrapper.html" class="code" title="">LSLWrapper</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="LSLWrapper.html" class="code" title="">LSLWrapper</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function LSL = LSLWrapper()</a></li><li><a href="#_sub2" class="code">function LSL = resolveStreams(LSL,datastream,maxbuffer,eventstream)</a></li><li><a href="#_sub3" class="code">function LSL = runExperiment(LSL)</a></li><li><a href="#_sub4" class="code">function LSL = visualizeDataStream(LSL,windowlength,datastreamname,channel)</a></li><li><a href="#_sub5" class="code">function streams = findStreams(LSL,timeout)</a></li><li><a href="#_sub6" class="code">function LSL = runSSVEP(LSL,eventStopCode)</a></li><li><a href="#_sub7" class="code">function wav = tts(txt,voice,pace,fs)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="LSLWrapper.m">LSLWrapper.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="LSLWrapper.html" class="code" title="">LSLWrapper</a> &lt; handle
+0002     <span class="comment">%LSLWRAPPER Summary of this class goes here</span>
+0003     <span class="comment">%   Detailed explanation goes here</span>
+0004     
+0005     properties
+0006         lib;
+0007         datastreaminfo;
+0008         datainlet;
+0009         dataoutlet;
+0010         eventstreaminfo;
+0011         eventinlet;
+0012         eventoutlet;
+0013         preprocessing;
+0014         featextraction;
+0015         results;
+0016         trials;
+0017         classification; <span class="comment">%pre-trained object required</span>
+0018     <span class="keyword">end</span>
+0019     
+0020     properties (Access = private)
+0021         streamsOK;
+0022         samplingRate;
+0023     <span class="keyword">end</span>
+0024     
+0025     methods
+0026         <a name="_sub0" href="#_subfunctions" class="code">function LSL = LSLWrapper()</a>
+0027             LSL.lib = lsl_loadlib;
+0028             LSL.streamsOK = 0;
+0029         <span class="keyword">end</span>
+0030         
+0031         <a name="_sub1" href="#_subfunctions" class="code">function LSL = resolveStreams(LSL,datastream,maxbuffer,eventstream)</a>
+0032             LSL.datastreaminfo = lsl_resolve_byprop(LSL.lib, <span class="string">'name'</span>, datastream);
+0033             LSL.eventstreaminfo = lsl_resolve_byprop(LSL.lib, <span class="string">'name'</span>, eventstream);
+0034             <span class="comment">%get samplingRate from stream info</span>
+0035             <span class="comment">%samplingRate = ?</span>
+0036             <span class="keyword">if</span>(length(LSL.datastreaminfo) &gt; 0)
+0037                 LSL.datainlet = lsl_inlet(LSL.datastreaminfo{1},maxbuffer);
+0038                 LSL.datainlet.pull_chunk;
+0039             <span class="keyword">else</span>
+0040                 error(<span class="string">'Cannot resolve data stream'</span>);
+0041             <span class="keyword">end</span>
+0042             <span class="keyword">if</span>(length(LSL.eventstreaminfo) &gt; 0)
+0043                 LSL.eventinlet = lsl_inlet(LSL.eventstreaminfo{1},1);
+0044             <span class="keyword">else</span>
+0045                 error(<span class="string">'Cannot resolve event stream'</span>);
+0046             <span class="keyword">end</span>
+0047             eventoutletInfo = lsl_streaminfo(LSL.lib,<span class="string">'CommandStream'</span>,<span class="string">'Markers'</span>,1,0,<span class="string">'cf_int32'</span>,<span class="string">'myuniquesourceid23442'</span>);
+0048             LSL.eventoutlet = lsl_outlet(eventoutletInfo);
+0049             LSL.samplingRate = LSL.datastreaminfo{1}.nominal_srate;
+0050             LSL.streamsOK = 1;
+0051         <span class="keyword">end</span>
+0052         <a name="_sub2" href="#_subfunctions" class="code">function LSL = runExperiment(LSL)</a>
+0053             <span class="keyword">if</span>(LSL.streamsOK ~=1)
+0054                 error(<span class="string">'error: Did you call \&quot;resolveStreams\&quot;?'</span>);
+0055             <span class="keyword">end</span>
+0056             strings = {<span class="string">'abstract'</span>,<span class="string">'concept'</span>,<span class="string">'objectives'</span>,<span class="string">'structure'</span>,<span class="string">'consortium'</span>};
+0057             labels = {4,2,3,5,1,2,5,4,2,3,1,5,4,3,2,4,1,2,5,3,4,1,3,1,3};
+0058             [12 6.66 7.5 8.57 10];
+0059             8.57,6.66,7.5,10,12
+0060             <span class="comment">%structure,concept,objectives,consortiu,abstract</span>
+0061             LSL.trials = {};
+0062             [y,Fs] = audioread(<span class="string">'beep-07.wav'</span>);
+0063             <a href="#_sub7" class="code" title="subfunction wav = tts(txt,voice,pace,fs)">tts</a>(<span class="string">'get ready'</span>);
+0064             pause(10);
+0065             <span class="keyword">for</span> i=1:length(labels)
+0066                 <a href="#_sub7" class="code" title="subfunction wav = tts(txt,voice,pace,fs)">tts</a>(strings{labels{i}});
+0067                 pause(1);
+0068                 sound(y,Fs);
+0069                 pause(5);
+0070                 
+0071                 chunk = LSL.datainlet.pull_chunk;
+0072                 trial = eegtoolkit.util.Trial(chunk,0,LSL.samplingRate,0,0);
+0073                 LSL.trials{length(LSL.trials)+1} = trial;
+0074                 <a href="#_sub7" class="code" title="subfunction wav = tts(txt,voice,pace,fs)">tts</a>(<span class="string">'ok'</span>);
+0075                 pause(4);
+0076             <span class="keyword">end</span>
+0077         <span class="keyword">end</span>
+0078         <span class="comment">%EBNeuro_BePLusLTM_192.168.171.81</span>
+0079         <a name="_sub3" href="#_subfunctions" class="code">function LSL = visualizeDataStream(LSL,windowlength,datastreamname,channel)</a>
+0080             <span class="comment">%             import java.util.Qu</span>
+0081             LSL.datastreaminfo = lsl_resolve_byprop(LSL.lib, <span class="string">'name'</span>, datastreamname);
+0082             LSL.datainlet = lsl_inlet(LSL.datastreaminfo{1},windowlength/LSL.datastreaminfo{1}.nominal_srate);
+0083             <span class="comment">%             LSL.eventstreaminfo = lsl_resolve_byprop(LSL.lib,'name',eventstreamname);</span>
+0084             
+0085             <span class="comment">%             buffer = eegtoolkit.util.CQueue(windowlength);</span>
+0086             <span class="comment">% %             buffer.capacity = windowlength;</span>
+0087             buffer = zeros(1,windowlength);
+0088             timestampBuffer = zeros(1,windowlength);
+0089             eventBuffer = zeros(1,windowlength);
+0090             indices = 1:windowlength;
+0091             t = 0 ;
+0092             x = 0 ;
+0093             startSpot = 0;
+0094             <span class="comment">%             interv = windowlength; % considering 1000 samples</span>
+0095             step = 0.1 ; <span class="comment">% lowering step has a number of cycles and then acquire more data</span>
+0096             k =1;
+0097             firstTimestamp = [];
+0098             <span class="keyword">while</span> ( 1 )
+0099                 <span class="comment">%                 sample = LSL.datainlet.pull_sample;</span>
+0100                 [samples,timestamps] = LSL.datainlet.pull_chunk;
+0101                 <span class="keyword">if</span> isempty(firstTimestamp)
+0102                     firstTimestamp = timestamps;
+0103                 <span class="keyword">end</span>
+0104                 [~,numPulled] = size(samples);
+0105                 <span class="keyword">if</span>(numPulled==0)
+0106                     <span class="keyword">continue</span>;
+0107                 <span class="keyword">end</span>
+0108                 <span class="comment">%                 buffer.push(sample(1));</span>
+0109                 <span class="comment">%                 buffermat = cell2mat(buffer.content);</span>
+0110                 buffer = circshift(buffer,[1,-numPulled]);
+0111                 timestampBuffer = circshift(timestampBuffer,[1,-numPulled]);
+0112                 buffer(windowlength-numPulled+1:end) = samples(channel,:);
+0113                 timestampBuffer(windowlength-numPulled+1:end) = timestamps-firstTimestamp;
+0114                 <span class="comment">%                 buffer(windowlength) = sample(1);</span>
+0115                 minBuff = min(buffer(buffer~=0));
+0116                 maxBuff = max(buffer(buffer~=0));
+0117                 plot(timestampBuffer,buffer);
+0118                 axis([ timestampBuffer(1), timestampBuffer(end)+1, minBuff , maxBuff+1 ]);
+0119                 xlabel(<span class="string">'Seconds'</span>);
+0120                 <span class="comment">%                 axis([ timestampBuffer(1), timestampBuffer(end), minBuff , maxBuff ]);</span>
+0121                 grid
+0122                 
+0123                 t = t + step;
+0124                 drawnow;
+0125                 k = k+1;
+0126                 <span class="comment">%                 indices = indices + 1;</span>
+0127                 <span class="comment">%                 pause(0.01)</span>
+0128             <span class="keyword">end</span>
+0129         <span class="keyword">end</span>
+0130         
+0131         <a name="_sub4" href="#_subfunctions" class="code">function streams = findStreams(LSL,timeout)</a>
+0132             streams = {};
+0133             <span class="keyword">if</span>(nargin&gt;1)
+0134                 allInfo = lsl_resolve_all(LSL.lib,timeout);
+0135             <span class="keyword">else</span>
+0136                 allInfo = lsl_resolve_all(LSL.lib);
+0137             <span class="keyword">end</span>
+0138             <span class="keyword">for</span> i=1:length(allInfo)
+0139                 streams{i} = allInfo{i}.name;
+0140             <span class="keyword">end</span>
+0141         <span class="keyword">end</span>
+0142         <a name="_sub5" href="#_subfunctions" class="code">function LSL = runSSVEP(LSL,eventStopCode)</a>
+0143             <span class="keyword">if</span> (LSL.streamsOK ~=1)
+0144                 error(<span class="string">'error: Did you call \&quot;resolveStreams\&quot; ?'</span>);
+0145             <span class="keyword">end</span>
+0146             <span class="keyword">while</span> 1
+0147                 sample = LSL.eventinlet.pull_sample;
+0148                 disp([<span class="string">'sample = '</span>, num2str(sample)]);
+0149                 <span class="keyword">if</span>(sample==eventStopCode)
+0150                     <span class="comment">%                     disp('Collecting signal...');</span>
+0151                     pause(5);
+0152                     <span class="comment">%                     disp('Processing...');</span>
+0153                     chunk = LSL.datainlet.pull_chunk;
+0154                     trial = {eegtoolkit.util.Trial(chunk,0,LSL.samplingRate,0,0)};
+0155                     <span class="keyword">for</span> i=1:length(LSL.preprocessing)
+0156                         trial = LSL.preprocessing{i}.process(trial);
+0157                     <span class="keyword">end</span>
+0158                     LSL.featextraction.trials = trial;
+0159                     LSL.featextraction.extract;
+0160                     [output, prob, rank] = LSL.classification.classifyInstance(LSL.featextraction.getInstances);
+0161                     result = 0;
+0162                     <span class="comment">%                     plot(chunk')</span>
+0163                     rank
+0164                     LSL.results = [LSL.results,output];
+0165                     disp([<span class="string">'classif output = '</span>, num2str(output)]);
+0166                     <span class="comment">%                     LSL.eventoutlet.push_sample(output);</span>
+0167                     LSL.eventoutlet.push_sample(output-1);
+0168                     <span class="comment">%                     disp(['prob = ', num2str(prob)]);</span>
+0169                 <span class="keyword">end</span>
+0170             <span class="keyword">end</span>
+0171         <span class="keyword">end</span>
+0172         
+0173     <span class="keyword">end</span>
+0174     
+0175     methods(Access = private)
+0176         <a name="_sub6" href="#_subfunctions" class="code">function wav = tts(txt,voice,pace,fs)</a>
+0177             <span class="comment">%TTS text to speech.</span>
+0178             <span class="comment">%   TTS (TXT) synthesizes speech from string TXT, and speaks it. The audio</span>
+0179             <span class="comment">%   format is mono, 16 bit, 16k Hz by default.</span>
+0180             <span class="comment">%</span>
+0181             <span class="comment">%   WAV = TTS(TXT) does not vocalize but output to the variable WAV.</span>
+0182             <span class="comment">%</span>
+0183             <span class="comment">%   TTS(TXT,VOICE) uses the specific voice. Use TTS('','List') to see a</span>
+0184             <span class="comment">%   list of availble voices. Default is the first voice.</span>
+0185             <span class="comment">%</span>
+0186             <span class="comment">%   TTS(...,PACE) set the pace of speech to PACE. PACE ranges from</span>
+0187             <span class="comment">%   -10 (slowest) to 10 (fastest). Default 0.</span>
+0188             <span class="comment">%</span>
+0189             <span class="comment">%   TTS(...,FS) set the sampling rate of the speech to FS kHz. FS must be</span>
+0190             <span class="comment">%   one of the following: 8000, 11025, 12000, 16000, 22050, 24000, 32000,</span>
+0191             <span class="comment">%       44100, 48000. Default 16.</span>
+0192             <span class="comment">%</span>
+0193             <span class="comment">%   This function requires the Microsoft Win32 Speech API (SAPI).</span>
+0194             <span class="comment">%</span>
+0195             <span class="comment">%   Examples:</span>
+0196             <span class="comment">%       % Speak the text;</span>
+0197             <span class="comment">%       tts('I can speak.');</span>
+0198             <span class="comment">%       % List availble voices;</span>
+0199             <span class="comment">%       tts('I can speak.','List');</span>
+0200             <span class="comment">%       % Do not speak out, store the speech in a variable;</span>
+0201             <span class="comment">%       w = tts('I can speak.',[],-4,44100);</span>
+0202             <span class="comment">%       wavplay(w,44100);</span>
+0203             <span class="comment">%</span>
+0204             <span class="comment">%   See also WAVREAD, WAVWRITE, WAVPLAY.</span>
+0205             
+0206             <span class="comment">% Written by Siyi Deng; 12-21-2007;</span>
+0207             
+0208             <span class="keyword">if</span> ~ispc, error(<span class="string">'Microsoft Win32 SAPI is required.'</span>); <span class="keyword">end</span>
+0209             <span class="keyword">if</span> ~ischar(txt), error(<span class="string">'First input must be string.'</span>); <span class="keyword">end</span>
+0210             
+0211             SV = actxserver(<span class="string">'SAPI.SpVoice'</span>);
+0212             TK = invoke(SV,<span class="string">'GetVoices'</span>);
+0213             
+0214             <span class="keyword">if</span> nargin &gt; 1
+0215                 <span class="comment">% Select voice;</span>
+0216                 <span class="keyword">for</span> k = 0:TK.Count-1
+0217                     <span class="keyword">if</span> strcmpi(voice,TK.Item(k).GetDescription)
+0218                         SV.Voice = TK.Item(k);
+0219                         <span class="keyword">break</span>;
+0220                     <span class="keyword">elseif</span> strcmpi(voice,<span class="string">'list'</span>)
+0221                         disp(TK.Item(k).GetDescription);
+0222                     <span class="keyword">end</span>
+0223                 <span class="keyword">end</span>
+0224                 <span class="comment">% Set pace;</span>
+0225                 <span class="keyword">if</span> nargin &gt; 2
+0226                     <span class="keyword">if</span> isempty(pace), pace = 0; <span class="keyword">end</span>
+0227                     <span class="keyword">if</span> abs(pace) &gt; 10, pace = sign(pace)*10; <span class="keyword">end</span>
+0228                     SV.Rate = pace;
+0229                 <span class="keyword">end</span>
+0230             <span class="keyword">end</span>
+0231             
+0232             <span class="keyword">if</span> nargin &lt; 4 || ~ismember(fs,[8000,11025,12000,16000,22050,24000,32000,<span class="keyword">...</span>
+0233                     44100,48000]), fs = 16000; <span class="keyword">end</span>
+0234             
+0235             <span class="keyword">if</span> nargout &gt; 0
+0236                 <span class="comment">% Output variable;</span>
+0237                 MS = actxserver(<span class="string">'SAPI.SpMemoryStream'</span>);
+0238                 MS.Format.Type = sprintf(<span class="string">'SAFT%dkHz16BitMono'</span>,fix(fs/1000));
+0239                 SV.AudioOutputStream = MS;
+0240             <span class="keyword">end</span>
+0241             
+0242             invoke(SV,<span class="string">'Speak'</span>,txt);
+0243             
+0244             <span class="keyword">if</span> nargout &gt; 0
+0245                 <span class="comment">% Convert uint8 to double precision;</span>
+0246                 wav = reshape(double(invoke(MS,<span class="string">'GetData'</span>)),2,[])';
+0247                 wav = (wav(:,2)*256+wav(:,1))/32768;
+0248                 wav(wav &gt;= 1) = wav(wav &gt;= 1)-2;
+0249                 delete(MS);
+0250                 clear MS;
+0251             <span class="keyword">end</span>
+0252             
+0253             delete(SV);
+0254             clear SV TK;
+0255             pause(0.2);
+0256             
+0257         <span class="keyword">end</span> <span class="comment">% TTS;</span>
+0258     <span class="keyword">end</span>
+0259 <span class="keyword">end</span>
+0260</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.m b/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.m
new file mode 100644
index 0000000..92166c1
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.m
@@ -0,0 +1,260 @@
+classdef LSLWrapper < handle
+    %LSLWRAPPER Summary of this class goes here
+    %   Detailed explanation goes here
+    
+    properties
+        lib;
+        datastreaminfo;
+        datainlet;
+        dataoutlet;
+        eventstreaminfo;
+        eventinlet;
+        eventoutlet;
+        preprocessing;
+        featextraction;
+        results;
+        trials;
+        classification; %pre-trained object required
+    end
+    
+    properties (Access = private)
+        streamsOK;
+        samplingRate;
+    end
+    
+    methods
+        function LSL = LSLWrapper()
+            LSL.lib = lsl_loadlib;
+            LSL.streamsOK = 0;
+        end
+        
+        function LSL = resolveStreams(LSL,datastream,maxbuffer,eventstream)
+            LSL.datastreaminfo = lsl_resolve_byprop(LSL.lib, 'name', datastream);
+            LSL.eventstreaminfo = lsl_resolve_byprop(LSL.lib, 'name', eventstream);
+            %get samplingRate from stream info
+            %samplingRate = ?
+            if(length(LSL.datastreaminfo) > 0)
+                LSL.datainlet = lsl_inlet(LSL.datastreaminfo{1},maxbuffer);
+                LSL.datainlet.pull_chunk;
+            else
+                error('Cannot resolve data stream');
+            end
+            if(length(LSL.eventstreaminfo) > 0)
+                LSL.eventinlet = lsl_inlet(LSL.eventstreaminfo{1},1);
+            else
+                error('Cannot resolve event stream');
+            end
+            eventoutletInfo = lsl_streaminfo(LSL.lib,'CommandStream','Markers',1,0,'cf_int32','myuniquesourceid23442');
+            LSL.eventoutlet = lsl_outlet(eventoutletInfo);
+            LSL.samplingRate = LSL.datastreaminfo{1}.nominal_srate;
+            LSL.streamsOK = 1;
+        end
+        function LSL = runExperiment(LSL)
+            if(LSL.streamsOK ~=1)
+                error('error: Did you call \"resolveStreams\"?');
+            end
+            strings = {'abstract','concept','objectives','structure','consortium'};
+            labels = {4,2,3,5,1,2,5,4,2,3,1,5,4,3,2,4,1,2,5,3,4,1,3,1,3};
+            [12 6.66 7.5 8.57 10];
+            8.57,6.66,7.5,10,12
+            %structure,concept,objectives,consortiu,abstract
+            LSL.trials = {};
+            [y,Fs] = audioread('beep-07.wav');
+            tts('get ready');
+            pause(10);
+            for i=1:length(labels)
+                tts(strings{labels{i}});
+                pause(1);
+                sound(y,Fs);
+                pause(5);
+                
+                chunk = LSL.datainlet.pull_chunk;
+                trial = eegtoolkit.util.Trial(chunk,0,LSL.samplingRate,0,0);
+                LSL.trials{length(LSL.trials)+1} = trial;
+                tts('ok');
+                pause(4);
+            end
+        end
+        %EBNeuro_BePLusLTM_192.168.171.81
+        function LSL = visualizeDataStream(LSL,windowlength,datastreamname,channel)
+            %             import java.util.Qu
+            LSL.datastreaminfo = lsl_resolve_byprop(LSL.lib, 'name', datastreamname);
+            LSL.datainlet = lsl_inlet(LSL.datastreaminfo{1},windowlength/LSL.datastreaminfo{1}.nominal_srate);
+            %             LSL.eventstreaminfo = lsl_resolve_byprop(LSL.lib,'name',eventstreamname);
+            
+            %             buffer = eegtoolkit.util.CQueue(windowlength);
+            % %             buffer.capacity = windowlength;
+            buffer = zeros(1,windowlength);
+            timestampBuffer = zeros(1,windowlength);
+            eventBuffer = zeros(1,windowlength);
+            indices = 1:windowlength;
+            t = 0 ;
+            x = 0 ;
+            startSpot = 0;
+            %             interv = windowlength; % considering 1000 samples
+            step = 0.1 ; % lowering step has a number of cycles and then acquire more data
+            k =1;
+            firstTimestamp = [];
+            while ( 1 )
+                %                 sample = LSL.datainlet.pull_sample;
+                [samples,timestamps] = LSL.datainlet.pull_chunk;
+                if isempty(firstTimestamp)
+                    firstTimestamp = timestamps;
+                end
+                [~,numPulled] = size(samples);
+                if(numPulled==0)
+                    continue;
+                end
+                %                 buffer.push(sample(1));
+                %                 buffermat = cell2mat(buffer.content);
+                buffer = circshift(buffer,[1,-numPulled]);
+                timestampBuffer = circshift(timestampBuffer,[1,-numPulled]);
+                buffer(windowlength-numPulled+1:end) = samples(channel,:);
+                timestampBuffer(windowlength-numPulled+1:end) = timestamps-firstTimestamp;
+                %                 buffer(windowlength) = sample(1);
+                minBuff = min(buffer(buffer~=0));
+                maxBuff = max(buffer(buffer~=0));
+                plot(timestampBuffer,buffer);
+                axis([ timestampBuffer(1), timestampBuffer(end)+1, minBuff , maxBuff+1 ]);
+                xlabel('Seconds');
+                %                 axis([ timestampBuffer(1), timestampBuffer(end), minBuff , maxBuff ]);
+                grid
+                
+                t = t + step;
+                drawnow;
+                k = k+1;
+                %                 indices = indices + 1;
+                %                 pause(0.01)
+            end
+        end
+        
+        function streams = findStreams(LSL,timeout)
+            streams = {};
+            if(nargin>1)
+                allInfo = lsl_resolve_all(LSL.lib,timeout);
+            else
+                allInfo = lsl_resolve_all(LSL.lib);
+            end
+            for i=1:length(allInfo)
+                streams{i} = allInfo{i}.name;
+            end
+        end
+        function LSL = runSSVEP(LSL,eventStopCode)
+            if (LSL.streamsOK ~=1)
+                error('error: Did you call \"resolveStreams\" ?');
+            end
+            while 1
+                sample = LSL.eventinlet.pull_sample;
+                disp(['sample = ', num2str(sample)]);
+                if(sample==eventStopCode)
+                    %                     disp('Collecting signal...');
+                    pause(5);
+                    %                     disp('Processing...');
+                    chunk = LSL.datainlet.pull_chunk;
+                    trial = {eegtoolkit.util.Trial(chunk,0,LSL.samplingRate,0,0)};
+                    for i=1:length(LSL.preprocessing)
+                        trial = LSL.preprocessing{i}.process(trial);
+                    end
+                    LSL.featextraction.trials = trial;
+                    LSL.featextraction.extract;
+                    [output, prob, rank] = LSL.classification.classifyInstance(LSL.featextraction.getInstances);
+                    result = 0;
+                    %                     plot(chunk')
+                    rank
+                    LSL.results = [LSL.results,output];
+                    disp(['classif output = ', num2str(output)]);
+                    %                     LSL.eventoutlet.push_sample(output);
+                    LSL.eventoutlet.push_sample(output-1);
+                    %                     disp(['prob = ', num2str(prob)]);
+                end
+            end
+        end
+        
+    end
+    
+    methods(Access = private)
+        function wav = tts(txt,voice,pace,fs)
+            %TTS text to speech.
+            %   TTS (TXT) synthesizes speech from string TXT, and speaks it. The audio
+            %   format is mono, 16 bit, 16k Hz by default.
+            %
+            %   WAV = TTS(TXT) does not vocalize but output to the variable WAV.
+            %
+            %   TTS(TXT,VOICE) uses the specific voice. Use TTS('','List') to see a
+            %   list of availble voices. Default is the first voice.
+            %
+            %   TTS(...,PACE) set the pace of speech to PACE. PACE ranges from
+            %   -10 (slowest) to 10 (fastest). Default 0.
+            %
+            %   TTS(...,FS) set the sampling rate of the speech to FS kHz. FS must be
+            %   one of the following: 8000, 11025, 12000, 16000, 22050, 24000, 32000,
+            %       44100, 48000. Default 16.
+            %
+            %   This function requires the Microsoft Win32 Speech API (SAPI).
+            %
+            %   Examples:
+            %       % Speak the text;
+            %       tts('I can speak.');
+            %       % List availble voices;
+            %       tts('I can speak.','List');
+            %       % Do not speak out, store the speech in a variable;
+            %       w = tts('I can speak.',[],-4,44100);
+            %       wavplay(w,44100);
+            %
+            %   See also WAVREAD, WAVWRITE, WAVPLAY.
+            
+            % Written by Siyi Deng; 12-21-2007;
+            
+            if ~ispc, error('Microsoft Win32 SAPI is required.'); end
+            if ~ischar(txt), error('First input must be string.'); end
+            
+            SV = actxserver('SAPI.SpVoice');
+            TK = invoke(SV,'GetVoices');
+            
+            if nargin > 1
+                % Select voice;
+                for k = 0:TK.Count-1
+                    if strcmpi(voice,TK.Item(k).GetDescription)
+                        SV.Voice = TK.Item(k);
+                        break;
+                    elseif strcmpi(voice,'list')
+                        disp(TK.Item(k).GetDescription);
+                    end
+                end
+                % Set pace;
+                if nargin > 2
+                    if isempty(pace), pace = 0; end
+                    if abs(pace) > 10, pace = sign(pace)*10; end
+                    SV.Rate = pace;
+                end
+            end
+            
+            if nargin < 4 || ~ismember(fs,[8000,11025,12000,16000,22050,24000,32000,...
+                    44100,48000]), fs = 16000; end
+            
+            if nargout > 0
+                % Output variable;
+                MS = actxserver('SAPI.SpMemoryStream');
+                MS.Format.Type = sprintf('SAFT%dkHz16BitMono',fix(fs/1000));
+                SV.AudioOutputStream = MS;
+            end
+            
+            invoke(SV,'Speak',txt);
+            
+            if nargout > 0
+                % Convert uint8 to double precision;
+                wav = reshape(double(invoke(MS,'GetData')),2,[])';
+                wav = (wav(:,2)*256+wav(:,1))/32768;
+                wav(wav >= 1) = wav(wav >= 1)-2;
+                delete(MS);
+                clear MS;
+            end
+            
+            delete(SV);
+            clear SV TK;
+            pause(0.2);
+            
+        end % TTS;
+    end
+end
+
diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/graph.dot b/doc/+eegtoolkit/+util/@LSLWrapper/graph.dot
new file mode 100644
index 0000000..8119234
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  LSLWrapper -> LSLWrapper;
+
+  LSLWrapper [URL="LSLWrapper.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/graph.html b/doc/+eegtoolkit/+util/@LSLWrapper/graph.html
new file mode 100644
index 0000000..1e471f6
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@LSLWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@LSLWrapper">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@LSLWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@LSLWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@LSLWrapper</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@LSLWrapper" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="LSLWrapper.html" title="LSLWrapper" alt="" coords="158,29,155,22,144,15,127,10,105,7,81,5,57,7,36,10,19,15,8,22,4,29,8,37,19,43,36,49,57,52,81,53,105,52,127,49,144,43,155,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/graph.map b/doc/+eegtoolkit/+util/@LSLWrapper/graph.map
new file mode 100644
index 0000000..b230ed0
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="LSLWrapper.html" title="LSLWrapper" alt="" coords="158,29,155,22,144,15,127,10,105,7,81,5,57,7,36,10,19,15,8,22,4,29,8,37,19,43,36,49,57,52,81,53,105,52,127,49,144,43,155,37">
diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/graph.png b/doc/+eegtoolkit/+util/@LSLWrapper/graph.png
new file mode 100644
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diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/index.html b/doc/+eegtoolkit/+util/@LSLWrapper/index.html
new file mode 100644
index 0000000..2c5d79d
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@LSLWrapper/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@LSLWrapper</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@LSLWrapper">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@LSLWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@LSLWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@LSLWrapper</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="LSLWrapper.html">LSLWrapper</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.html b/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.html
new file mode 100644
index 0000000..8cbbe7c
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.html
@@ -0,0 +1,112 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of RawSignalSet</title>
+  <meta name="keywords" content="RawSignalSet">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@RawSignalSet</a> &gt; RawSignalSet.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@RawSignalSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>RawSignalSet
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="RawSignalSet.html" class="code" title="">RawSignalSet</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="RawSignalSet.html" class="code" title="">RawSignalSet</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function RSS = RawSignalSet(trials)</a></li><li><a href="#_sub2" class="code">function sMatrix = get(indices)</a></li><li><a href="#_sub3" class="code">function sMatrix = getInstancesWithIndices(RSS,indices)</a></li><li><a href="#_sub4" class="code">function instanceStruct = removeInstancesWithIndices(RSS,indices)</a></li><li><a href="#_sub5" class="code">function numInstances = getNumInstances(RSS)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="RawSignalSet.m">RawSignalSet.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="RawSignalSet.html" class="code" title="">RawSignalSet</a> &lt; eegtoolkit.util.InstanceSet
+0002     <span class="comment">%RAWSIGNALSET Summary of this class goes here</span>
+0003     <span class="comment">%   Detailed explanation goes here</span>
+0004     
+0005     properties
+0006         <span class="comment">%numTrials X numChannels X numSamples</span>
+0007         signalMatrix;
+0008     <span class="keyword">end</span>
+0009     
+0010     methods
+0011         <a name="_sub0" href="#_subfunctions" class="code">function RSS = RawSignalSet(trials)</a>
+0012             <span class="comment">%             RSS = RSS@eegtoolkit.util.InstanceSet(zeros(1,1000),ones(1,1000));</span>
+0013             <span class="keyword">if</span>(nargin~=1)
+0014                 error(<span class="string">'trials parameter not set'</span>);
+0015             <span class="keyword">end</span>
+0016             <span class="comment">%             if(nargin&gt;0)</span>
+0017             numTrials = length(trials);
+0018             labels = zeros(numTrials,1);
+0019             <span class="keyword">for</span> i=1:numTrials
+0020                 labels(i) = trials{i}.label;
+0021             <span class="keyword">end</span>
+0022             [numChannels, numSamples] = size(trials{i}.signal);
+0023             sMatrix = zeros(numTrials,numChannels,numSamples);
+0024             <span class="keyword">for</span> i=1:numTrials
+0025                 sMatrix(i,:,:) = trials{i}.signal;
+0026             <span class="keyword">end</span>
+0027             RSS = RSS@eegtoolkit.util.InstanceSet(squeeze(sMatrix(:,1,:)),labels);
+0028             RSS.signalMatrix = sMatrix;
+0029             <span class="comment">%             end</span>
+0030         <span class="keyword">end</span>
+0031         
+0032         <a name="_sub1" href="#_subfunctions" class="code">function sMatrix = get(indices)</a>
+0033             sMatrix = squeeze(RSS.signalMatrix(indices,:,:));
+0034         <span class="keyword">end</span>
+0035         
+0036         <a name="_sub2" href="#_subfunctions" class="code">function sMatrix = getInstancesWithIndices(RSS,indices)</a>
+0037             sMatrix = RSS.signalMatrix(indices,:,:);
+0038         <span class="keyword">end</span>
+0039         
+0040         <a name="_sub3" href="#_subfunctions" class="code">function instanceStruct = removeInstancesWithIndices(RSS,indices)</a>
+0041 <span class="comment">%             newRSS = eegtoolkit.util.RawSignalSet;</span>
+0042 <span class="comment">%             newRSS.labels = RSS.labels;</span>
+0043 <span class="comment">%             newRSS.labels(indices) = [];</span>
+0044 <span class="comment">%             newRSS.signalMatrix = RSS.signalMatrix;</span>
+0045 <span class="comment">%             newRSS.signalMatrix(indices,:,:) = [];</span>
+0046             sMatrix = RSS.signalMatrix;
+0047             sMatrix(indices,:,:) = [];
+0048             
+0049             labels = RSS.labels;
+0050             labels(indices) = [];
+0051             instanceStruct = struct(<span class="string">'sMatrix'</span>,sMatrix, <span class="string">'labels'</span>, labels);
+0052         <span class="keyword">end</span>
+0053         
+0054         <a name="_sub4" href="#_subfunctions" class="code">function numInstances = getNumInstances(RSS)</a>
+0055             [numInstances,~,~] = size(RSS.signalMatrix);
+0056         <span class="keyword">end</span>
+0057             
+0058     <span class="keyword">end</span>
+0059     
+0060     
+0061 <span class="keyword">end</span>
+0062</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.m b/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.m
new file mode 100644
index 0000000..4f963a7
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@RawSignalSet/RawSignalSet.m
@@ -0,0 +1,62 @@
+classdef RawSignalSet < eegtoolkit.util.InstanceSet
+    %RAWSIGNALSET Summary of this class goes here
+    %   Detailed explanation goes here
+    
+    properties
+        %numTrials X numChannels X numSamples
+        signalMatrix;
+    end
+    
+    methods
+        function RSS = RawSignalSet(trials)
+            %             RSS = RSS@eegtoolkit.util.InstanceSet(zeros(1,1000),ones(1,1000));
+            if(nargin~=1)
+                error('trials parameter not set');
+            end
+            %             if(nargin>0)
+            numTrials = length(trials);
+            labels = zeros(numTrials,1);
+            for i=1:numTrials
+                labels(i) = trials{i}.label;
+            end
+            [numChannels, numSamples] = size(trials{i}.signal);
+            sMatrix = zeros(numTrials,numChannels,numSamples);
+            for i=1:numTrials
+                sMatrix(i,:,:) = trials{i}.signal;
+            end
+            RSS = RSS@eegtoolkit.util.InstanceSet(squeeze(sMatrix(:,1,:)),labels);
+            RSS.signalMatrix = sMatrix;
+            %             end
+        end
+        
+        function sMatrix = get(indices)
+            sMatrix = squeeze(RSS.signalMatrix(indices,:,:));
+        end
+        
+        function sMatrix = getInstancesWithIndices(RSS,indices)
+            sMatrix = RSS.signalMatrix(indices,:,:);
+        end
+        
+        function instanceStruct = removeInstancesWithIndices(RSS,indices)
+%             newRSS = eegtoolkit.util.RawSignalSet;
+%             newRSS.labels = RSS.labels;
+%             newRSS.labels(indices) = [];
+%             newRSS.signalMatrix = RSS.signalMatrix;
+%             newRSS.signalMatrix(indices,:,:) = [];
+            sMatrix = RSS.signalMatrix;
+            sMatrix(indices,:,:) = [];
+            
+            labels = RSS.labels;
+            labels(indices) = [];
+            instanceStruct = struct('sMatrix',sMatrix, 'labels', labels);
+        end
+        
+        function numInstances = getNumInstances(RSS)
+            [numInstances,~,~] = size(RSS.signalMatrix);
+        end
+            
+    end
+    
+    
+end
+    
diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/graph.dot b/doc/+eegtoolkit/+util/@RawSignalSet/graph.dot
new file mode 100644
index 0000000..c3e43b9
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@RawSignalSet/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  RawSignalSet -> RawSignalSet;
+
+  RawSignalSet [URL="RawSignalSet.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/graph.html b/doc/+eegtoolkit/+util/@RawSignalSet/graph.html
new file mode 100644
index 0000000..6eddfe1
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@RawSignalSet/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@RawSignalSet</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@RawSignalSet">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@RawSignalSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@RawSignalSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@RawSignalSet</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@RawSignalSet" border="2" style="color:#000;">  
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+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/graph.map b/doc/+eegtoolkit/+util/@RawSignalSet/graph.map
new file mode 100644
index 0000000..880bbfc
--- /dev/null
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diff --git a/doc/+eegtoolkit/+util/@RawSignalSet/index.html b/doc/+eegtoolkit/+util/@RawSignalSet/index.html
new file mode 100644
index 0000000..d84e8cd
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@RawSignalSet/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@RawSignalSet</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@RawSignalSet">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@RawSignalSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@RawSignalSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@RawSignalSet</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="RawSignalSet.html">RawSignalSet</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@ResultSet/ResultSet.html b/doc/+eegtoolkit/+util/@ResultSet/ResultSet.html
new file mode 100644
index 0000000..0f798a2
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@ResultSet/ResultSet.html
@@ -0,0 +1,111 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of ResultSet</title>
+  <meta name="keywords" content="ResultSet">
+  <meta name="description" content="RESULTSET class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@ResultSet</a> &gt; ResultSet.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@ResultSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>ResultSet
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>RESULTSET class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> RESULTSET class
+ Stores the results of an experiment</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ResultSet.html" class="code" title="">ResultSet</a>	RESULTSET class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="ResultSet.html" class="code" title="">ResultSet</a>	RESULTSET class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function RS = ResultSet(instanceSet, labels, probabilities, ranking)</a></li><li><a href="#_sub2" class="code">function RSSubset = subset(RS,indices)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="ResultSet.m">ResultSet.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% RESULTSET class</span>
+0002 <span class="comment">% Stores the results of an experiment</span>
+0003 classdef <a href="ResultSet.html" class="code" title="">ResultSet</a> &lt; eegtoolkit.util.InstanceSet
+0004     
+0005     properties
+0006         outputLabels; <span class="comment">% The output labels</span>
+0007         outputProbabilities; <span class="comment">% Probabilities</span>
+0008         outputRanking; <span class="comment">% Confidence scores</span>
+0009         confusionMatrix; <span class="comment">% The Confusion Matrix</span>
+0010     <span class="keyword">end</span>
+0011     
+0012     methods
+0013         <a name="_sub0" href="#_subfunctions" class="code">function RS = ResultSet(instanceSet, labels, probabilities, ranking)</a>
+0014             <span class="comment">%Constructor method</span>
+0015             <span class="comment">%Input:</span>
+0016             <span class="comment">%(InstanceSet object): the original instanceSet</span>
+0017             <span class="comment">%Labels: a vector containing the output labels of the</span>
+0018             <span class="comment">%experiment</span>
+0019             <span class="comment">%Proababilities: a vector containing the probabilities of each</span>
+0020             <span class="comment">%label</span>
+0021             <span class="comment">%Ranking (optional): a matrix containing a score for each label</span>
+0022             
+0023             RS = RS@eegtoolkit.util.InstanceSet(instanceSet);
+0024             RS.outputLabels = labels;
+0025 
+0026             <span class="comment">%compute the confusion matrix</span>
+0027             labels = unique(RS.getLabels);
+0028             numLabels = length(labels);
+0029             RS.confusionMatrix = zeros(numLabels);
+0030             trueLabels = RS.getLabels;
+0031             numInstances = RS.getNumInstances;
+0032             <span class="keyword">for</span> k=1:numInstances
+0033                 idx1 = find(labels==RS.outputLabels(k,1));
+0034                 idx2 = find(labels==trueLabels(k,1));
+0035                 RS.confusionMatrix(idx1,idx2) = RS.confusionMatrix(idx1,idx2)+ 1;
+0036             <span class="keyword">end</span>
+0037             RS.confusionMatrix = RS.confusionMatrix';
+0038             <span class="comment">%if classifier supports ranking/probabilities</span>
+0039             <span class="keyword">if</span> nargin &gt; 2
+0040                 RS.outputProbabilities = probabilities;
+0041                 RS.outputRanking = ranking;
+0042             <span class="keyword">end</span>
+0043         <span class="keyword">end</span>
+0044         
+0045         <a name="_sub1" href="#_subfunctions" class="code">function RSSubset = subset(RS,indices)</a>
+0046             sOutputLabels = RS.outputLabels(indices);
+0047             sOutputProbabilities = RS.outputProbabilities(indices);
+0048             sInstanceSet = RS.getDatasetWithIndices(indices);
+0049             <span class="keyword">if</span> isempty(RS.outputProbabilities)
+0050                 RSSubset = eegtoolkit.util.ResultSet(sInstanceSet,sOutputLabels,sOutputProbabilities);
+0051             <span class="keyword">else</span>
+0052                 sOutputRanking = RS.outputRanking(indices);
+0053                 RSSubset = eegtoolkit.util.ResultSet(sInstanceSet,sOutputLabels,sOutputProbabilities,sOutputRanking);
+0054             <span class="keyword">end</span>
+0055         <span class="keyword">end</span>
+0056             
+0057     <span class="keyword">end</span>
+0058     
+0059 <span class="keyword">end</span>
+0060</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@ResultSet/ResultSet.m b/doc/+eegtoolkit/+util/@ResultSet/ResultSet.m
new file mode 100644
index 0000000..01513b4
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@ResultSet/ResultSet.m
@@ -0,0 +1,60 @@
+% RESULTSET class
+% Stores the results of an experiment
+classdef ResultSet < eegtoolkit.util.InstanceSet
+    
+    properties
+        outputLabels; % The output labels 
+        outputProbabilities; % Probabilities
+        outputRanking; % Confidence scores
+        confusionMatrix; % The Confusion Matrix
+    end
+    
+    methods
+        function RS = ResultSet(instanceSet, labels, probabilities, ranking)
+            %Constructor method
+            %Input:
+            %(InstanceSet object): the original instanceSet
+            %Labels: a vector containing the output labels of the
+            %experiment
+            %Proababilities: a vector containing the probabilities of each
+            %label
+            %Ranking (optional): a matrix containing a score for each label
+            
+            RS = RS@eegtoolkit.util.InstanceSet(instanceSet);
+            RS.outputLabels = labels;
+
+            %compute the confusion matrix
+            labels = unique(RS.getLabels);
+            numLabels = length(labels);
+            RS.confusionMatrix = zeros(numLabels);
+            trueLabels = RS.getLabels;
+            numInstances = RS.getNumInstances;
+            for k=1:numInstances
+                idx1 = find(labels==RS.outputLabels(k,1));
+                idx2 = find(labels==trueLabels(k,1));
+                RS.confusionMatrix(idx1,idx2) = RS.confusionMatrix(idx1,idx2)+ 1;
+            end
+            RS.confusionMatrix = RS.confusionMatrix';
+            %if classifier supports ranking/probabilities
+            if nargin > 2
+                RS.outputProbabilities = probabilities;
+                RS.outputRanking = ranking;
+            end
+        end
+        
+        function RSSubset = subset(RS,indices)
+            sOutputLabels = RS.outputLabels(indices);
+            sOutputProbabilities = RS.outputProbabilities(indices);
+            sInstanceSet = RS.getDatasetWithIndices(indices);
+            if isempty(RS.outputProbabilities)
+                RSSubset = eegtoolkit.util.ResultSet(sInstanceSet,sOutputLabels,sOutputProbabilities);
+            else
+                sOutputRanking = RS.outputRanking(indices);
+                RSSubset = eegtoolkit.util.ResultSet(sInstanceSet,sOutputLabels,sOutputProbabilities,sOutputRanking);
+            end
+        end
+            
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+util/@ResultSet/graph.dot b/doc/+eegtoolkit/+util/@ResultSet/graph.dot
new file mode 100644
index 0000000..08f05cc
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@ResultSet/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  ResultSet -> ResultSet;
+
+  ResultSet [URL="ResultSet.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@ResultSet/graph.html b/doc/+eegtoolkit/+util/@ResultSet/graph.html
new file mode 100644
index 0000000..1eee7e5
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@ResultSet/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@ResultSet</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@ResultSet">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@ResultSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@ResultSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@ResultSet</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@ResultSet" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="ResultSet.html" title="ResultSet" alt="" coords="123,29,120,22,112,15,99,10,82,7,64,5,46,7,29,10,16,15,8,22,5,29,8,37,16,43,29,49,46,52,64,53,82,52,99,49,112,43,120,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@ResultSet/graph.map b/doc/+eegtoolkit/+util/@ResultSet/graph.map
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diff --git a/doc/+eegtoolkit/+util/@ResultSet/index.html b/doc/+eegtoolkit/+util/@ResultSet/index.html
new file mode 100644
index 0000000..2f90638
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@ResultSet/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@ResultSet</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@ResultSet">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@ResultSet">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@ResultSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@ResultSet</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="ResultSet.html">ResultSet</a></td><td>RESULTSET class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Session/Session.html b/doc/+eegtoolkit/+util/@Session/Session.html
new file mode 100644
index 0000000..ccb7732
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/Session.html
@@ -0,0 +1,589 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Session</title>
+  <meta name="keywords" content="Session">
+  <meta name="description" content="SESSION class">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@Session</a> &gt; Session.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Session
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>SESSION class</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> SESSION class
+ Session I/O, splitting sessions into trials and applying filters
+
+ Properties:
+ trials: A cell array with the Trials of the loaded sessions.
+ filt: Filter to be applied when data is loaded
+ sessions: Cell array with the filenames of the dataset
+ subjectids: Vector with the subject ids corresponding to the loaded trials
+ sessionids: Vector with the session ids corresponding to the loaded trials
+
+ Functions:
+init a session
+   session = eegtoolkit.util.Session();
+init a session with a filter (created with 'filterbuilder')
+   session = eegtoolkit.util.Session(filt);
+load trials for a subject
+   session.loadSubject(subjectid);
+load a specific session
+   session.loadSubjectSession(subjectid,sessionid);
+load everything
+   session.loadAll();
+clear loaded data
+   session.clearData;
+apply a filter that was created with 'filterbuilder'
+   session.applyFilter(filt);
+
+
+DATASETS
+1. SSVEP Dataset I (SINGLE)
+2. SSVEP Dataset II (MULTI)
+3. SSVEP Dataset III (EPOC-MULTI)
+4. SSVEP Dataset SCCN
+5. ERRP Dataset
+6. MI Dataset</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Session.html" class="code" title="">Session</a>	SESSION class</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Session.html" class="code" title="">Session</a>	SESSION class</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function S = Session()</a></li><li><a href="#_sub2" class="code">function S = loadAll(S,experiment)</a></li><li><a href="#_sub3" class="code">function S = loadSubject(S,experiment,subject)</a></li><li><a href="#_sub4" class="code">function S = loadSubjectSession(S,experiment,subject,session)</a></li><li><a href="#_sub5" class="code">function S = clearData(S)</a></li><li><a href="#_sub6" class="code">function trials = split(S, signal, dins, subjectid, session,labels)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Session.m">Session.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% SESSION class</span>
+0002 <span class="comment">% Session I/O, splitting sessions into trials and applying filters</span>
+0003 <span class="comment">%</span>
+0004 <span class="comment">% Properties:</span>
+0005 <span class="comment">% trials: A cell array with the Trials of the loaded sessions.</span>
+0006 <span class="comment">% filt: Filter to be applied when data is loaded</span>
+0007 <span class="comment">% sessions: Cell array with the filenames of the dataset</span>
+0008 <span class="comment">% subjectids: Vector with the subject ids corresponding to the loaded trials</span>
+0009 <span class="comment">% sessionids: Vector with the session ids corresponding to the loaded trials</span>
+0010 <span class="comment">%</span>
+0011 <span class="comment">% Functions:</span>
+0012 <span class="comment">%init a session</span>
+0013 <span class="comment">%   session = eegtoolkit.util.Session();</span>
+0014 <span class="comment">%init a session with a filter (created with 'filterbuilder')</span>
+0015 <span class="comment">%   session = eegtoolkit.util.Session(filt);</span>
+0016 <span class="comment">%load trials for a subject</span>
+0017 <span class="comment">%   session.loadSubject(subjectid);</span>
+0018 <span class="comment">%load a specific session</span>
+0019 <span class="comment">%   session.loadSubjectSession(subjectid,sessionid);</span>
+0020 <span class="comment">%load everything</span>
+0021 <span class="comment">%   session.loadAll();</span>
+0022 <span class="comment">%clear loaded data</span>
+0023 <span class="comment">%   session.clearData;</span>
+0024 <span class="comment">%apply a filter that was created with 'filterbuilder'</span>
+0025 <span class="comment">%   session.applyFilter(filt);</span>
+0026 <span class="comment">%</span>
+0027 <span class="comment">%</span>
+0028 <span class="comment">%DATASETS</span>
+0029 <span class="comment">%1. SSVEP Dataset I (SINGLE)</span>
+0030 <span class="comment">%2. SSVEP Dataset II (MULTI)</span>
+0031 <span class="comment">%3. SSVEP Dataset III (EPOC-MULTI)</span>
+0032 <span class="comment">%4. SSVEP Dataset SCCN</span>
+0033 <span class="comment">%5. ERRP Dataset</span>
+0034 <span class="comment">%6. MI Dataset</span>
+0035 
+0036 classdef <a href="Session.html" class="code" title="">Session</a> &lt; handle
+0037     
+0038     properties (Constant)
+0039         THRESHOLD_SPLIT_MILLIS = 2000; <span class="comment">%Threshold for splitting the trials based on DIN data</span>
+0040     <span class="keyword">end</span>
+0041     properties (Access = public)
+0042         trials = {}; <span class="comment">% Trials of the loaded sessions.</span>
+0043         filt; <span class="comment">% Filter to be applied when data is loaded</span>
+0044         sessions; <span class="comment">% Filenames of the dataset</span>
+0045         subjectids; <span class="comment">% The subject ids corresponding to the loaded trials</span>
+0046         sessionids;
+0047     <span class="keyword">end</span>
+0048     
+0049     
+0050     methods (Access = public)
+0051         <a name="_sub0" href="#_subfunctions" class="code">function S = Session()</a>
+0052             <span class="comment">%S = eegtoolkit.util.Session();</span>
+0053             <span class="comment">%Constructs a session object</span>
+0054             <span class="comment">%</span>
+0055             <span class="comment">%S = eegtoolkit.util.Session(filt);</span>
+0056             <span class="comment">%Constructs a session object. A filter will applied to all</span>
+0057             <span class="comment">%loaded trials</span>
+0058             <span class="comment">%Dataset I</span>
+0059             S.sessions{1,1,1} = <span class="string">'S001a'</span>;
+0060             S.sessions{1,1,2} = <span class="string">'S001b'</span>;
+0061             S.sessions{1,1,3} = <span class="string">'S001c'</span>;
+0062             S.sessions{1,2,1} = <span class="string">'S002a'</span>;
+0063             S.sessions{1,2,2} = <span class="string">'S002b'</span>;
+0064             S.sessions{1,2,3} = <span class="string">'S002c'</span>;
+0065             S.sessions{1,2,4} = <span class="string">'S002d'</span>;
+0066             S.sessions{1,2,5} = <span class="string">'S002e'</span>;
+0067             S.sessions{1,3,1} = <span class="string">'S003a'</span>;
+0068             S.sessions{1,3,2} = <span class="string">'S003b'</span>;
+0069             S.sessions{1,3,3} = <span class="string">'S003c'</span>;
+0070             S.sessions{1,4,1} = <span class="string">'S004a'</span>;
+0071             S.sessions{1,4,2} = <span class="string">'S004b'</span>;
+0072             S.sessions{1,4,3} = <span class="string">'S004c'</span>;
+0073             S.sessions{1,4,4} = <span class="string">'S004d'</span>;
+0074             S.sessions{1,5,1} = <span class="string">'S005a'</span>;
+0075             S.sessions{1,5,2} = <span class="string">'S005b'</span>;
+0076             S.sessions{1,5,3} = <span class="string">'S005c'</span>;
+0077             S.sessions{1,5,4} = <span class="string">'S005d'</span>;
+0078             S.sessions{1,5,5} = <span class="string">'S005e'</span>;
+0079             S.sessions{1,6,1} = <span class="string">'S006a'</span>;
+0080             S.sessions{1,6,2} = <span class="string">'S006b'</span>;
+0081             S.sessions{1,6,3} = <span class="string">'S006c'</span>;
+0082             S.sessions{1,6,4} = <span class="string">'S006d'</span>;
+0083             S.sessions{1,6,5} = <span class="string">'S006e'</span>;
+0084             S.sessions{1,7,1} = <span class="string">'S007a'</span>;
+0085             S.sessions{1,7,2} = <span class="string">'S007b'</span>;
+0086             S.sessions{1,7,3} = <span class="string">'S007c'</span>;
+0087             S.sessions{1,7,4} = <span class="string">'S007d'</span>;
+0088             S.sessions{1,7,5} = <span class="string">'S007e'</span>;
+0089             S.sessions{1,8,1} = <span class="string">'S008a'</span>;
+0090             S.sessions{1,8,2} = <span class="string">'S008b'</span>;
+0091             S.sessions{1,8,3} = <span class="string">'S008c'</span>;
+0092             S.sessions{1,9,1} = <span class="string">'S009a'</span>;
+0093             S.sessions{1,9,2} = <span class="string">'S009b'</span>;
+0094             S.sessions{1,9,3} = <span class="string">'S009c'</span>;
+0095             S.sessions{1,9,4} = <span class="string">'S009d'</span>;
+0096             S.sessions{1,9,5} = <span class="string">'S009e'</span>;
+0097             S.sessions{1,10,1} = <span class="string">'S010a'</span>;
+0098             S.sessions{1,10,2} = <span class="string">'S010b'</span>;
+0099             S.sessions{1,10,3} = <span class="string">'S010c'</span>;
+0100             S.sessions{1,10,4} = <span class="string">'S010d'</span>;
+0101             S.sessions{1,10,5} = <span class="string">'S010e'</span>;
+0102             S.sessions{1,11,1} = <span class="string">'S013a'</span>;
+0103             S.sessions{1,11,2} = <span class="string">'S013b'</span>;
+0104             S.sessions{1,11,3} = <span class="string">'S013c'</span>;
+0105             S.sessions{1,11,4} = <span class="string">'S013d'</span>;
+0106             S.sessions{1,11,5} = <span class="string">'S013e'</span>;
+0107             
+0108             <span class="comment">%Dataset II</span>
+0109             S.sessions{2,1,1} = <span class="string">'T001a'</span>;
+0110             S.sessions{2,1,2} = <span class="string">'T001b'</span>;
+0111             S.sessions{2,1,3} = <span class="string">'T001c'</span>;
+0112             S.sessions{2,1,4} = <span class="string">'T001d'</span>;
+0113             S.sessions{2,1,5} = <span class="string">'T001e'</span>;
+0114             S.sessions{2,2,1} = <span class="string">'T002a'</span>;
+0115             S.sessions{2,2,2} = <span class="string">'T002b'</span>;
+0116             S.sessions{2,2,3} = <span class="string">'T002c'</span>;
+0117             S.sessions{2,2,4} = <span class="string">'T002d'</span>;
+0118             S.sessions{2,2,5} = <span class="string">'T002e'</span>;
+0119             S.sessions{2,3,1} = <span class="string">'T003a'</span>;
+0120             S.sessions{2,3,2} = <span class="string">'T003b'</span>;
+0121             S.sessions{2,3,3} = <span class="string">'T003c'</span>;
+0122             S.sessions{2,3,4} = <span class="string">'T003d'</span>;
+0123             S.sessions{2,3,5} = <span class="string">'T003e'</span>;
+0124             S.sessions{2,4,1} = <span class="string">'T004a'</span>;
+0125             S.sessions{2,4,2} = <span class="string">'T004b'</span>;
+0126             S.sessions{2,4,3} = <span class="string">'T004c'</span>;
+0127             S.sessions{2,4,4} = <span class="string">'T004d'</span>;
+0128             S.sessions{2,4,5} = <span class="string">'T004e'</span>;
+0129             S.sessions{2,5,1} = <span class="string">'T005a'</span>;
+0130             S.sessions{2,5,2} = <span class="string">'T005b'</span>;
+0131             S.sessions{2,5,3} = <span class="string">'T005c'</span>;
+0132             S.sessions{2,5,4} = <span class="string">'T005d'</span>;
+0133             S.sessions{2,5,5} = <span class="string">'T005e'</span>;
+0134             S.sessions{2,6,1} = <span class="string">'T006a'</span>;
+0135             S.sessions{2,6,2} = <span class="string">'T006b'</span>;
+0136             S.sessions{2,6,3} = <span class="string">'T006c'</span>;
+0137             S.sessions{2,6,4} = <span class="string">'T006d'</span>;
+0138             S.sessions{2,6,5} = <span class="string">'T006e'</span>;
+0139             S.sessions{2,7,1} = <span class="string">'T007a'</span>;
+0140             S.sessions{2,7,2} = <span class="string">'T007b'</span>;
+0141             S.sessions{2,7,3} = <span class="string">'T007c'</span>;
+0142             S.sessions{2,7,4} = <span class="string">'T007d'</span>;
+0143             S.sessions{2,7,5} = <span class="string">'T007e'</span>;
+0144             S.sessions{2,8,1} = <span class="string">'T008a'</span>;
+0145             S.sessions{2,8,2} = <span class="string">'T008b'</span>;
+0146             S.sessions{2,8,3} = <span class="string">'T008c'</span>;
+0147             S.sessions{2,8,4} = <span class="string">'T008d'</span>;
+0148             S.sessions{2,8,5} = <span class="string">'T008e'</span>;
+0149             S.sessions{2,9,1} = <span class="string">'T009a'</span>;
+0150             S.sessions{2,9,2} = <span class="string">'T009b'</span>;
+0151             S.sessions{2,9,3} = <span class="string">'T009c'</span>;
+0152             S.sessions{2,9,4} = <span class="string">'T009d'</span>;
+0153             S.sessions{2,9,5} = <span class="string">'T009e'</span>;
+0154             S.sessions{2,10,1} = <span class="string">'T010a'</span>;
+0155             S.sessions{2,10,2} = <span class="string">'T010b'</span>;
+0156             S.sessions{2,10,3} = <span class="string">'T010c'</span>;
+0157             S.sessions{2,10,4} = <span class="string">'T010d'</span>;
+0158             S.sessions{2,10,5} = <span class="string">'T010e'</span>;
+0159             S.sessions{2,11,1} = <span class="string">'T013a'</span>;
+0160             S.sessions{2,11,2} = <span class="string">'T013b'</span>;
+0161             S.sessions{2,11,3} = <span class="string">'T013c'</span>;
+0162             S.sessions{2,11,4} = <span class="string">'T013d'</span>;
+0163             S.sessions{2,11,5} = <span class="string">'T013e'</span>;
+0164             
+0165             <span class="comment">%Dataset III (Epoc)</span>
+0166             S.sessions{3,1,1} = <span class="string">'U001a'</span>;
+0167             S.sessions{3,1,2} = <span class="string">'U001b'</span>;
+0168             S.sessions{3,1,3} = <span class="string">'U001c'</span>;
+0169             S.sessions{3,1,4} = <span class="string">'U001d'</span>;
+0170             S.sessions{3,1,5} = <span class="string">'U001e'</span>;
+0171             S.sessions{3,2,1} = <span class="string">'U002a'</span>;
+0172             S.sessions{3,2,2} = <span class="string">'U002b'</span>;
+0173             S.sessions{3,2,3} = <span class="string">'U002c'</span>;
+0174             S.sessions{3,2,4} = <span class="string">'U002d'</span>;
+0175             S.sessions{3,2,5} = <span class="string">'U002e'</span>;
+0176             S.sessions{3,3,1} = <span class="string">'U003a'</span>;
+0177             S.sessions{3,3,2} = <span class="string">'U003b'</span>;
+0178             S.sessions{3,3,3} = <span class="string">'U003c'</span>;
+0179             S.sessions{3,3,4} = <span class="string">'U003d'</span>;
+0180             S.sessions{3,3,5} = <span class="string">'U003e'</span>;
+0181             S.sessions{3,4,1} = <span class="string">'U004a'</span>;
+0182             S.sessions{3,4,2} = <span class="string">'U004b'</span>;
+0183             S.sessions{3,4,3} = <span class="string">'U004c'</span>;
+0184             S.sessions{3,4,4} = <span class="string">'U004d'</span>;
+0185             S.sessions{3,4,5} = <span class="string">'U004e'</span>;
+0186             S.sessions{3,5,1} = <span class="string">'U005a'</span>;
+0187             S.sessions{3,5,2} = <span class="string">'U005b'</span>;
+0188             S.sessions{3,5,3} = <span class="string">'U005c'</span>;
+0189             S.sessions{3,5,4} = <span class="string">'U005d'</span>;
+0190             S.sessions{3,5,5} = <span class="string">'U005e'</span>;
+0191             S.sessions{3,6,1} = <span class="string">'U006a'</span>;
+0192             S.sessions{3,6,2} = <span class="string">'U006b'</span>;
+0193             S.sessions{3,6,3} = <span class="string">'U006c'</span>;
+0194             S.sessions{3,6,4} = <span class="string">'U006d'</span>;
+0195             S.sessions{3,6,5} = <span class="string">'U006e'</span>;
+0196             S.sessions{3,7,1} = <span class="string">'U007a'</span>;
+0197             S.sessions{3,7,2} = <span class="string">'U007b'</span>;
+0198             S.sessions{3,7,3} = <span class="string">'U007c'</span>;
+0199             S.sessions{3,7,4} = <span class="string">'U007d'</span>;
+0200             S.sessions{3,7,5} = <span class="string">'U007e'</span>;
+0201             S.sessions{3,8,1} = <span class="string">'U008a'</span>;
+0202             S.sessions{3,8,2} = <span class="string">'U008b'</span>;
+0203             S.sessions{3,8,3} = <span class="string">'U008c'</span>;
+0204             S.sessions{3,8,4} = <span class="string">'U008d'</span>;
+0205             S.sessions{3,8,5} = <span class="string">'U008e'</span>;
+0206             S.sessions{3,9,1} = <span class="string">'U009a'</span>;
+0207             S.sessions{3,9,2} = <span class="string">'U009b'</span>;
+0208             S.sessions{3,9,3} = <span class="string">'U009c'</span>;
+0209             S.sessions{3,9,4} = <span class="string">'U009d'</span>;
+0210             S.sessions{3,9,5} = <span class="string">'U009e'</span>;
+0211             S.sessions{3,10,1} = <span class="string">'U010a'</span>;
+0212             S.sessions{3,10,2} = <span class="string">'U010b'</span>;
+0213             S.sessions{3,10,3} = <span class="string">'U010c'</span>;
+0214             S.sessions{3,10,4} = <span class="string">'U010d'</span>;
+0215             S.sessions{3,10,5} = <span class="string">'U010e'</span>;
+0216             S.sessions{3,11,1} = <span class="string">'U011a'</span>;
+0217             S.sessions{3,11,2} = <span class="string">'U011b'</span>;
+0218             S.sessions{3,11,3} = <span class="string">'U011c'</span>;
+0219             S.sessions{3,11,4} = <span class="string">'U011d'</span>;
+0220             S.sessions{3,11,5} = <span class="string">'U011e'</span>;
+0221             
+0222             <span class="comment">%SCCN dataset</span>
+0223             S.sessions{4,1,1} = <span class="string">'s1'</span>;
+0224             S.sessions{4,2,1} = <span class="string">'s2'</span>;
+0225             S.sessions{4,3,1} = <span class="string">'s3'</span>;
+0226             S.sessions{4,4,1} = <span class="string">'s4'</span>;
+0227             S.sessions{4,5,1} = <span class="string">'s5'</span>;
+0228             S.sessions{4,6,1} = <span class="string">'s6'</span>;
+0229             S.sessions{4,7,1} = <span class="string">'s7'</span>;
+0230             S.sessions{4,8,1} = <span class="string">'s8'</span>;
+0231             S.sessions{4,9,1} = <span class="string">'s9'</span>;
+0232             S.sessions{4,10,1} = <span class="string">'s10'</span>;
+0233             
+0234             <span class="comment">%ERRP dataset</span>
+0235             S.sessions{5,1,1} = <span class="string">'EEG_s1.mat'</span>;
+0236             S.sessions{5,2,1} = <span class="string">'EEG_s2.mat'</span>;
+0237             S.sessions{5,3,1} = <span class="string">'EEG_s3.mat'</span>;
+0238             S.sessions{5,4,1} = <span class="string">'EEG_s4.mat'</span>;
+0239             S.sessions{5,5,1} = <span class="string">'EEG_s5.mat'</span>;
+0240             S.sessions{5,6,1} = <span class="string">'EEG_s6.mat'</span>;
+0241             S.sessions{5,7,1} = <span class="string">'EEG_s7.mat'</span>;
+0242             S.sessions{5,8,1} = <span class="string">'EEG_s8.mat'</span>;
+0243             
+0244             S.sessions{6,1,1} = <span class="string">'dataset_BCIcomp1.mat'</span>;
+0245             
+0246             S.sessions{7,1,1} = <span class="string">'B01T.mat'</span>;
+0247             S.sessions{7,1,2} = <span class="string">'B01T.mat'</span>;
+0248             S.sessions{7,2,1} = <span class="string">'B02T.mat'</span>;
+0249             S.sessions{7,2,2} = <span class="string">'B02T.mat'</span>;
+0250             S.sessions{7,3,1} = <span class="string">'B03T.mat'</span>;
+0251             S.sessions{7,3,2} = <span class="string">'B03T.mat'</span>;
+0252             S.sessions{7,4,1} = <span class="string">'B04T.mat'</span>;
+0253             S.sessions{7,4,2} = <span class="string">'B04T.mat'</span>;
+0254             S.sessions{7,5,1} = <span class="string">'B05T.mat'</span>;
+0255             S.sessions{7,5,2} = <span class="string">'B05T.mat'</span>;
+0256             S.sessions{7,6,1} = <span class="string">'B06T.mat'</span>;
+0257             S.sessions{7,6,2} = <span class="string">'B06T.mat'</span>;
+0258             S.sessions{7,7,1} = <span class="string">'B07T.mat'</span>;
+0259             S.sessions{7,7,2} = <span class="string">'B07T.mat'</span>;
+0260             S.sessions{7,8,1} = <span class="string">'B08T.mat'</span>;
+0261             S.sessions{7,8,2} = <span class="string">'B08T.mat'</span>;
+0262             S.sessions{7,9,1} = <span class="string">'B09T.mat'</span>;
+0263             S.sessions{7,9,2} = <span class="string">'B09T.mat'</span>;
+0264             
+0265             <span class="comment">%MI dataset</span>
+0266             <span class="comment">%             S.sessions{6,1,1} = ;</span>
+0267             
+0268             
+0269             S.subjectids = [];
+0270             S.sessionids = [];
+0271         <span class="keyword">end</span>
+0272         <a name="_sub1" href="#_subfunctions" class="code">function S = loadAll(S,experiment)</a>
+0273             <span class="comment">%loads everything</span>
+0274             [~,l,~] = size(S.sessions);
+0275             h = waitbar(0,<span class="string">'Loading...'</span>);
+0276             <span class="keyword">for</span> i=1:l
+0277                 waitbar(i/l,h,<span class="string">'Loading...'</span>);
+0278                 S.loadSubject(experiment,i);
+0279             <span class="keyword">end</span>
+0280             close(h);
+0281         <span class="keyword">end</span>
+0282         
+0283         <a name="_sub2" href="#_subfunctions" class="code">function S = loadSubject(S,experiment,subject)</a>
+0284             <span class="comment">%loads all trials for a specific subject</span>
+0285             <span class="comment">%</span>
+0286             <span class="comment">%Example:</span>
+0287             <span class="comment">%   session.loadSubject(1);</span>
+0288             <span class="comment">%loads all the trials of the 1st subject</span>
+0289             [~,~, y] = size(S.sessions);
+0290             <span class="keyword">for</span> i=1:y
+0291                 <span class="keyword">if</span> ~isempty(S.sessions{experiment,subject,i})
+0292                     S.loadSubjectSession(experiment,subject,i);
+0293                 <span class="keyword">end</span>
+0294             <span class="keyword">end</span>
+0295         <span class="keyword">end</span>
+0296         <a name="_sub3" href="#_subfunctions" class="code">function S = loadSubjectSession(S,experiment,subject,session)</a>
+0297             <span class="comment">%loads all trials for a specific session</span>
+0298             <span class="comment">%</span>
+0299             <span class="comment">%Example:</span>
+0300             <span class="comment">%   session.loadSubjectSession(1,2);</span>
+0301             <span class="comment">%loads the 2nd session of the 1st subject</span>
+0302             <span class="comment">%</span>
+0303             <span class="keyword">switch</span>(experiment)
+0304                 <span class="keyword">case</span> 1
+0305                     <span class="comment">%Load Dataset I (SINGLE)</span>
+0306                     load(S.sessions{experiment,subject,session});
+0307                     signal = eval(<span class="string">'eeg'</span>);
+0308                     numTrials = length(S.trials) + 1;
+0309                     curTrials = S.split(signal,DIN_1,subject,session);
+0310                     <span class="keyword">for</span> i=1:length(curTrials)
+0311                         S.trials{numTrials} = curTrials{i};
+0312                         numTrials = numTrials + 1;
+0313                     <span class="keyword">end</span>
+0314                 <span class="keyword">case</span> 2
+0315                     <span class="comment">%Load Dataset II (MULTI)</span>
+0316                     load(S.sessions{experiment,subject,session});
+0317                     signal = eval(<span class="string">'eeg'</span>);
+0318                     numTrials = length(S.trials) + 1;
+0319                     curTrials = S.split(signal,DIN_1,subject,session,labels);
+0320                     <span class="keyword">for</span> i=1:length(curTrials)
+0321                         S.trials{numTrials} = curTrials{i};
+0322                         numTrials = numTrials + 1;
+0323                     <span class="keyword">end</span>
+0324                 <span class="keyword">case</span> 3
+0325                     <span class="comment">%Dataset III (EPOC-MULTI)</span>
+0326                     SAMPLING_RATE = 128;
+0327                     load(strcat(S.sessions{experiment,subject,session},<span class="string">'i'</span>));
+0328                     events = eval(<span class="string">'events'</span>);
+0329                     marks = events(events(:,2)==32779,3);
+0330                     stops = events(events(:,2)==32780,3);
+0331                     numTrials = length(S.trials) + 1;
+0332                     labels = {4,2,3,5,1,2,5,4,2,3,1,5};
+0333                     <span class="keyword">for</span> i=1:length(marks)
+0334                         signal = eeg(:,marks(i):stops(i) -1);
+0335                         label = labels{i};
+0336                         S.trials{numTrials} = eegtoolkit.util.Trial(signal,label,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.SSVEP);
+0337                         numTrials = numTrials + 1;
+0338                         S.subjectids = [S.subjectids subject];
+0339                         S.sessionids = [S.sessionids session];
+0340                     <span class="keyword">end</span>
+0341                     <span class="comment">%load part 2</span>
+0342                     load(strcat(S.sessions{experiment,subject,session},<span class="string">'ii'</span>));
+0343                     events = eval(<span class="string">'events'</span>);
+0344                     marks = events(events(:,2)==32779,3);
+0345                     stops = events(events(:,2)==32780,3);
+0346                     numTrials = length(S.trials) + 1;
+0347                     labels = {4,3,2,4,1,2,5,3,4,1,3,1,3};
+0348                     <span class="keyword">for</span> i=1:length(marks)
+0349                         signal = eeg(:,marks(i):stops(i) -1);
+0350                         label = labels{i};
+0351                         S.trials{numTrials} = eegtoolkit.util.Trial(signal,label,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.SSVEP);
+0352                         numTrials = numTrials + 1;
+0353                         S.subjectids = [S.subjectids subject];
+0354                         S.sessionids = [S.sessionids session];
+0355                     <span class="keyword">end</span>
+0356                 <span class="keyword">case</span> 4
+0357                     <span class="comment">%SCCN Dataset</span>
+0358                     SAMPLING_RATE = 256;
+0359                     load(S.sessions{experiment,subject,session});
+0360                     [x,y,z,zz] = size(eeg);
+0361                     numTrials = length(S.trials) + 1;
+0362                     <span class="keyword">for</span> i=1:x
+0363                         <span class="keyword">for</span> j=1:zz
+0364                             S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(eeg(i,:,:,j)),i,SAMPLING_RATE,subject,j);
+0365                             numTrials = numTrials+1;
+0366                             S.subjectids = [S.subjectids subject];
+0367                             S.sessionids = [S.sessionids j];
+0368                         <span class="keyword">end</span>
+0369                     <span class="keyword">end</span>
+0370                 <span class="keyword">case</span> 5
+0371                     <span class="comment">%ERRP Dataset</span>
+0372                     SAMPLING_RATE = 256;
+0373                     <span class="comment">%range of trial in milliseconds based on the stimulus</span>
+0374                     <span class="comment">%event</span>
+0375                     range = [200,800];
+0376                     xstart = round(range(1)*SAMPLING_RATE/1000)-1500;
+0377                     xend = round(range(2)*SAMPLING_RATE/1000);
+0378                     load(S.sessions{experiment,subject,session});
+0379                     events = {<span class="string">'correct_movement'</span>, <span class="string">'error_movement'</span>};
+0380                     numTrials = length(S.trials) + 1;
+0381                     <span class="keyword">for</span> ev=1:length(events)
+0382                         idxev = find(strcmp(EEG.events.name, events{ev}));
+0383                         epochs.(events{ev}) = zeros(length(xstart:xend), size(EEG.signal,2), length(idxev));
+0384                         <span class="keyword">for</span> i=1:length(idxev)
+0385                             epochs.(events{ev})(:,:,i) = EEG.signal(EEG.events.position(idxev(i))+xstart:EEG.events.position(idxev(i))+xend,:);
+0386                         <span class="keyword">end</span>
+0387                         GrandAverages.(events{ev}) = mean(epochs.(events{ev}),3);
+0388                     <span class="keyword">end</span>
+0389                     [~,~,numCorrect] = size(epochs.correct_movement);
+0390                     [~,~,numError] = size(epochs.error_movement);
+0391                     <span class="keyword">for</span> i=1:numCorrect
+0392                         S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(epochs.correct_movement(:,:,i))',1,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.ERRP);
+0393                         numTrials = numTrials + 1;
+0394                         S.subjectids = [S.subjectids subject];
+0395                         S.sessionids = [S.sessionids session];
+0396                         
+0397                     <span class="keyword">end</span>
+0398                     <span class="keyword">for</span> i=1:numError
+0399                         S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(epochs.error_movement(:,:,i))',2,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.ERRP);
+0400                         numTrials = numTrials + 1;
+0401                         S.subjectids = [S.subjectids subject];
+0402                         S.sessionids = [S.sessionids session];
+0403                     <span class="keyword">end</span>
+0404                 <span class="keyword">case</span> 6
+0405                     load(S.sessions{experiment,subject,session});
+0406                     [~,~,n] = size(x_train);
+0407                     numTrials = length(S.trials) + 1;
+0408                     <span class="keyword">for</span> i=1:n
+0409                         signal = squeeze(x_train(:,:,i));
+0410                         label = y_train(i);
+0411                         S.trials{numTrials} = eegtoolkit.util.Trial(signal',label,128,1,1,eegtoolkit.util.Trial.MI);
+0412                         S.subjectids = [S.subjectids subject];
+0413                         S.sessionids = [S.sessionids session];
+0414                         numTrials = numTrials + 1;
+0415                     <span class="keyword">end</span>
+0416                 <span class="keyword">case</span> 7
+0417                     load(S.sessions{experiment,subject,session});
+0418                     [trialsegm,labels] = segmentGratzB(data{session},0.5,2.5,250);
+0419                     [n,~,~] = size(trialsegm);
+0420                     numTrials = length(S.trials) + 1;
+0421                     <span class="keyword">for</span> i=1:n
+0422                         signal = squeeze(trialsegm(i,:,:));
+0423                         label = labels(i);
+0424                         S.trials{numTrials} = eegtoolkit.util.Trial(signal',label,250,subject,session,eegtoolkit.util.Trial.MI);
+0425                         S.subjectids = [S.subjectids subject];
+0426                         S.sessionids = [S.sessionids session];
+0427                         numTrials = numTrials + 1;
+0428                     <span class="keyword">end</span>
+0429                 <span class="keyword">otherwise</span>
+0430                     error(<span class="string">'invalid experiment id'</span>);
+0431             <span class="keyword">end</span>
+0432         <span class="keyword">end</span>
+0433         
+0434         <a name="_sub4" href="#_subfunctions" class="code">function S = clearData(S)</a>
+0435             <span class="comment">%clears loaded data</span>
+0436             S.trials = {};
+0437             S.subjectids = [];
+0438             S.sessionids = [];
+0439         <span class="keyword">end</span>
+0440     <span class="keyword">end</span>
+0441     
+0442     methods (Access = private)
+0443         <a name="_sub5" href="#_subfunctions" class="code">function trials = split(S, signal, dins, subjectid, session,labels)</a>
+0444             SAMPLING_RATE = 250;
+0445             timestamps = cell2mat(dins(2,:));
+0446             samples = cell2mat(dins(4,:));
+0447             [a numDins ]= size(dins);
+0448             sampleA= samples(1);
+0449             timeA = timestamps(1);
+0450             previous = timestamps(1);
+0451             ranges = [];
+0452             freqs = [];
+0453             times = [];
+0454             sum = 0;
+0455             count = 0;
+0456             i=2;
+0457             <span class="keyword">for</span> i=2:numDins
+0458                 current = timestamps(i);
+0459                 <span class="keyword">if</span>(current - previous) &gt; S.THRESHOLD_SPLIT_MILLIS;
+0460                     sampleB = samples(i-1);
+0461                     timeB = timestamps(i-1);
+0462                     freqs = [freqs; (sum/count)];
+0463                     <span class="comment">% don't ask why</span>
+0464                     <span class="keyword">if</span>(sampleB - sampleA&gt;382)
+0465                         ranges = [ranges ; [sampleA (sampleA+1249)]];
+0466                         times = [times; [timeA timeB]];
+0467                     <span class="keyword">end</span>
+0468                     sampleA = samples(i);
+0469                     timeA = timestamps(i);
+0470                     sum = 0;
+0471                     count = 0;
+0472                 <span class="keyword">else</span>
+0473                     sum = sum + (current-previous);
+0474                     count = count +1;
+0475                 <span class="keyword">end</span>
+0476                 previous = timestamps(i);
+0477             <span class="keyword">end</span>
+0478             <span class="comment">%             if(isempty(labels))</span>
+0479             sampleB = samples(i-1);
+0480             timeB = timestamps(i-1);
+0481             freqs = [freqs; (sum/count)];
+0482             ranges = [ranges; [sampleA sampleA+1249]];
+0483             times = [times; [timeA timeB]];
+0484             freqs = freqs*2;
+0485             freqs = 1000./freqs;
+0486             <span class="comment">%             end</span>
+0487             [numSplits a] = size(ranges);
+0488             trials = {};
+0489             i = 1;
+0490             <span class="keyword">for</span> i=1:numSplits
+0491                 <span class="keyword">if</span>(nargin&gt;5)
+0492                     trials{i} = eegtoolkit.util.Trial(signal(:, ranges(i,1):ranges(i,2)), labels{i},SAMPLING_RATE, subjectid,session,eegtoolkit.util.Trial.SSVEP);
+0493                     S.subjectids = [S.subjectids subjectid];
+0494                     S.sessionids = [S.sessionids session];
+0495                 <span class="keyword">else</span>
+0496                     trials{i} = eegtoolkit.util.Trial(signal(:,ranges(i,1):ranges(i,2)), freqs(i), SAMPLING_RATE, subjectid,session,eegtoolkit.util.Trial.SSVEP);
+0497                     S.subjectids = [S.subjectids subjectid];
+0498                     S.sessionids = [S.sessionids session];
+0499                 <span class="keyword">end</span>
+0500             <span class="keyword">end</span>
+0501         <span class="keyword">end</span>
+0502         
+0503         
+0504     <span class="keyword">end</span>
+0505 <span class="keyword">end</span>
+0506</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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diff --git a/doc/+eegtoolkit/+util/@Session/Session.m b/doc/+eegtoolkit/+util/@Session/Session.m
new file mode 100644
index 0000000..eb89757
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/Session.m
@@ -0,0 +1,506 @@
+% SESSION class
+% Session I/O, splitting sessions into trials and applying filters
+%
+% Properties:
+% trials: A cell array with the Trials of the loaded sessions.
+% filt: Filter to be applied when data is loaded
+% sessions: Cell array with the filenames of the dataset
+% subjectids: Vector with the subject ids corresponding to the loaded trials
+% sessionids: Vector with the session ids corresponding to the loaded trials
+%
+% Functions:
+%init a session
+%   session = eegtoolkit.util.Session();
+%init a session with a filter (created with 'filterbuilder')
+%   session = eegtoolkit.util.Session(filt);
+%load trials for a subject
+%   session.loadSubject(subjectid);
+%load a specific session
+%   session.loadSubjectSession(subjectid,sessionid);
+%load everything
+%   session.loadAll();
+%clear loaded data
+%   session.clearData;
+%apply a filter that was created with 'filterbuilder'
+%   session.applyFilter(filt);
+%
+%
+%DATASETS
+%1. SSVEP Dataset I (SINGLE)
+%2. SSVEP Dataset II (MULTI)
+%3. SSVEP Dataset III (EPOC-MULTI)
+%4. SSVEP Dataset SCCN
+%5. ERRP Dataset
+%6. MI Dataset
+
+classdef Session < handle
+    
+    properties (Constant)
+        THRESHOLD_SPLIT_MILLIS = 2000; %Threshold for splitting the trials based on DIN data
+    end
+    properties (Access = public)
+        trials = {}; % Trials of the loaded sessions.
+        filt; % Filter to be applied when data is loaded
+        sessions; % Filenames of the dataset
+        subjectids; % The subject ids corresponding to the loaded trials
+        sessionids;
+    end
+    
+    
+    methods (Access = public)
+        function S = Session()
+            %S = eegtoolkit.util.Session();
+            %Constructs a session object
+            %
+            %S = eegtoolkit.util.Session(filt);
+            %Constructs a session object. A filter will applied to all
+            %loaded trials
+            %Dataset I
+            S.sessions{1,1,1} = 'S001a';
+            S.sessions{1,1,2} = 'S001b';
+            S.sessions{1,1,3} = 'S001c';
+            S.sessions{1,2,1} = 'S002a';
+            S.sessions{1,2,2} = 'S002b';
+            S.sessions{1,2,3} = 'S002c';
+            S.sessions{1,2,4} = 'S002d';
+            S.sessions{1,2,5} = 'S002e';
+            S.sessions{1,3,1} = 'S003a';
+            S.sessions{1,3,2} = 'S003b';
+            S.sessions{1,3,3} = 'S003c';
+            S.sessions{1,4,1} = 'S004a';
+            S.sessions{1,4,2} = 'S004b';
+            S.sessions{1,4,3} = 'S004c';
+            S.sessions{1,4,4} = 'S004d';
+            S.sessions{1,5,1} = 'S005a';
+            S.sessions{1,5,2} = 'S005b';
+            S.sessions{1,5,3} = 'S005c';
+            S.sessions{1,5,4} = 'S005d';
+            S.sessions{1,5,5} = 'S005e';
+            S.sessions{1,6,1} = 'S006a';
+            S.sessions{1,6,2} = 'S006b';
+            S.sessions{1,6,3} = 'S006c';
+            S.sessions{1,6,4} = 'S006d';
+            S.sessions{1,6,5} = 'S006e';
+            S.sessions{1,7,1} = 'S007a';
+            S.sessions{1,7,2} = 'S007b';
+            S.sessions{1,7,3} = 'S007c';
+            S.sessions{1,7,4} = 'S007d';
+            S.sessions{1,7,5} = 'S007e';
+            S.sessions{1,8,1} = 'S008a';
+            S.sessions{1,8,2} = 'S008b';
+            S.sessions{1,8,3} = 'S008c';
+            S.sessions{1,9,1} = 'S009a';
+            S.sessions{1,9,2} = 'S009b';
+            S.sessions{1,9,3} = 'S009c';
+            S.sessions{1,9,4} = 'S009d';
+            S.sessions{1,9,5} = 'S009e';
+            S.sessions{1,10,1} = 'S010a';
+            S.sessions{1,10,2} = 'S010b';
+            S.sessions{1,10,3} = 'S010c';
+            S.sessions{1,10,4} = 'S010d';
+            S.sessions{1,10,5} = 'S010e';
+            S.sessions{1,11,1} = 'S013a';
+            S.sessions{1,11,2} = 'S013b';
+            S.sessions{1,11,3} = 'S013c';
+            S.sessions{1,11,4} = 'S013d';
+            S.sessions{1,11,5} = 'S013e';
+            
+            %Dataset II
+            S.sessions{2,1,1} = 'T001a';
+            S.sessions{2,1,2} = 'T001b';
+            S.sessions{2,1,3} = 'T001c';
+            S.sessions{2,1,4} = 'T001d';
+            S.sessions{2,1,5} = 'T001e';
+            S.sessions{2,2,1} = 'T002a';
+            S.sessions{2,2,2} = 'T002b';
+            S.sessions{2,2,3} = 'T002c';
+            S.sessions{2,2,4} = 'T002d';
+            S.sessions{2,2,5} = 'T002e';
+            S.sessions{2,3,1} = 'T003a';
+            S.sessions{2,3,2} = 'T003b';
+            S.sessions{2,3,3} = 'T003c';
+            S.sessions{2,3,4} = 'T003d';
+            S.sessions{2,3,5} = 'T003e';
+            S.sessions{2,4,1} = 'T004a';
+            S.sessions{2,4,2} = 'T004b';
+            S.sessions{2,4,3} = 'T004c';
+            S.sessions{2,4,4} = 'T004d';
+            S.sessions{2,4,5} = 'T004e';
+            S.sessions{2,5,1} = 'T005a';
+            S.sessions{2,5,2} = 'T005b';
+            S.sessions{2,5,3} = 'T005c';
+            S.sessions{2,5,4} = 'T005d';
+            S.sessions{2,5,5} = 'T005e';
+            S.sessions{2,6,1} = 'T006a';
+            S.sessions{2,6,2} = 'T006b';
+            S.sessions{2,6,3} = 'T006c';
+            S.sessions{2,6,4} = 'T006d';
+            S.sessions{2,6,5} = 'T006e';
+            S.sessions{2,7,1} = 'T007a';
+            S.sessions{2,7,2} = 'T007b';
+            S.sessions{2,7,3} = 'T007c';
+            S.sessions{2,7,4} = 'T007d';
+            S.sessions{2,7,5} = 'T007e';
+            S.sessions{2,8,1} = 'T008a';
+            S.sessions{2,8,2} = 'T008b';
+            S.sessions{2,8,3} = 'T008c';
+            S.sessions{2,8,4} = 'T008d';
+            S.sessions{2,8,5} = 'T008e';
+            S.sessions{2,9,1} = 'T009a';
+            S.sessions{2,9,2} = 'T009b';
+            S.sessions{2,9,3} = 'T009c';
+            S.sessions{2,9,4} = 'T009d';
+            S.sessions{2,9,5} = 'T009e';
+            S.sessions{2,10,1} = 'T010a';
+            S.sessions{2,10,2} = 'T010b';
+            S.sessions{2,10,3} = 'T010c';
+            S.sessions{2,10,4} = 'T010d';
+            S.sessions{2,10,5} = 'T010e';
+            S.sessions{2,11,1} = 'T013a';
+            S.sessions{2,11,2} = 'T013b';
+            S.sessions{2,11,3} = 'T013c';
+            S.sessions{2,11,4} = 'T013d';
+            S.sessions{2,11,5} = 'T013e';
+            
+            %Dataset III (Epoc)
+            S.sessions{3,1,1} = 'U001a';
+            S.sessions{3,1,2} = 'U001b';
+            S.sessions{3,1,3} = 'U001c';
+            S.sessions{3,1,4} = 'U001d';
+            S.sessions{3,1,5} = 'U001e';
+            S.sessions{3,2,1} = 'U002a';
+            S.sessions{3,2,2} = 'U002b';
+            S.sessions{3,2,3} = 'U002c';
+            S.sessions{3,2,4} = 'U002d';
+            S.sessions{3,2,5} = 'U002e';
+            S.sessions{3,3,1} = 'U003a';
+            S.sessions{3,3,2} = 'U003b';
+            S.sessions{3,3,3} = 'U003c';
+            S.sessions{3,3,4} = 'U003d';
+            S.sessions{3,3,5} = 'U003e';
+            S.sessions{3,4,1} = 'U004a';
+            S.sessions{3,4,2} = 'U004b';
+            S.sessions{3,4,3} = 'U004c';
+            S.sessions{3,4,4} = 'U004d';
+            S.sessions{3,4,5} = 'U004e';
+            S.sessions{3,5,1} = 'U005a';
+            S.sessions{3,5,2} = 'U005b';
+            S.sessions{3,5,3} = 'U005c';
+            S.sessions{3,5,4} = 'U005d';
+            S.sessions{3,5,5} = 'U005e';
+            S.sessions{3,6,1} = 'U006a';
+            S.sessions{3,6,2} = 'U006b';
+            S.sessions{3,6,3} = 'U006c';
+            S.sessions{3,6,4} = 'U006d';
+            S.sessions{3,6,5} = 'U006e';
+            S.sessions{3,7,1} = 'U007a';
+            S.sessions{3,7,2} = 'U007b';
+            S.sessions{3,7,3} = 'U007c';
+            S.sessions{3,7,4} = 'U007d';
+            S.sessions{3,7,5} = 'U007e';
+            S.sessions{3,8,1} = 'U008a';
+            S.sessions{3,8,2} = 'U008b';
+            S.sessions{3,8,3} = 'U008c';
+            S.sessions{3,8,4} = 'U008d';
+            S.sessions{3,8,5} = 'U008e';
+            S.sessions{3,9,1} = 'U009a';
+            S.sessions{3,9,2} = 'U009b';
+            S.sessions{3,9,3} = 'U009c';
+            S.sessions{3,9,4} = 'U009d';
+            S.sessions{3,9,5} = 'U009e';
+            S.sessions{3,10,1} = 'U010a';
+            S.sessions{3,10,2} = 'U010b';
+            S.sessions{3,10,3} = 'U010c';
+            S.sessions{3,10,4} = 'U010d';
+            S.sessions{3,10,5} = 'U010e';
+            S.sessions{3,11,1} = 'U011a';
+            S.sessions{3,11,2} = 'U011b';
+            S.sessions{3,11,3} = 'U011c';
+            S.sessions{3,11,4} = 'U011d';
+            S.sessions{3,11,5} = 'U011e';
+            
+            %SCCN dataset
+            S.sessions{4,1,1} = 's1';
+            S.sessions{4,2,1} = 's2';
+            S.sessions{4,3,1} = 's3';
+            S.sessions{4,4,1} = 's4';
+            S.sessions{4,5,1} = 's5';
+            S.sessions{4,6,1} = 's6';
+            S.sessions{4,7,1} = 's7';
+            S.sessions{4,8,1} = 's8';
+            S.sessions{4,9,1} = 's9';
+            S.sessions{4,10,1} = 's10';
+            
+            %ERRP dataset
+            S.sessions{5,1,1} = 'EEG_s1.mat';
+            S.sessions{5,2,1} = 'EEG_s2.mat';
+            S.sessions{5,3,1} = 'EEG_s3.mat';
+            S.sessions{5,4,1} = 'EEG_s4.mat';
+            S.sessions{5,5,1} = 'EEG_s5.mat';
+            S.sessions{5,6,1} = 'EEG_s6.mat';
+            S.sessions{5,7,1} = 'EEG_s7.mat';
+            S.sessions{5,8,1} = 'EEG_s8.mat';
+            
+            S.sessions{6,1,1} = 'dataset_BCIcomp1.mat';
+            
+            S.sessions{7,1,1} = 'B01T.mat';
+            S.sessions{7,1,2} = 'B01T.mat';
+            S.sessions{7,2,1} = 'B02T.mat';
+            S.sessions{7,2,2} = 'B02T.mat';
+            S.sessions{7,3,1} = 'B03T.mat';
+            S.sessions{7,3,2} = 'B03T.mat';
+            S.sessions{7,4,1} = 'B04T.mat';
+            S.sessions{7,4,2} = 'B04T.mat';
+            S.sessions{7,5,1} = 'B05T.mat';
+            S.sessions{7,5,2} = 'B05T.mat';
+            S.sessions{7,6,1} = 'B06T.mat';
+            S.sessions{7,6,2} = 'B06T.mat';
+            S.sessions{7,7,1} = 'B07T.mat';
+            S.sessions{7,7,2} = 'B07T.mat';
+            S.sessions{7,8,1} = 'B08T.mat';
+            S.sessions{7,8,2} = 'B08T.mat';
+            S.sessions{7,9,1} = 'B09T.mat';
+            S.sessions{7,9,2} = 'B09T.mat';
+            
+            %MI dataset
+            %             S.sessions{6,1,1} = ;
+            
+            
+            S.subjectids = [];
+            S.sessionids = [];
+        end
+        function S = loadAll(S,experiment)
+            %loads everything
+            [~,l,~] = size(S.sessions);
+            h = waitbar(0,'Loading...');
+            for i=1:l
+                waitbar(i/l,h,'Loading...');
+                S.loadSubject(experiment,i);
+            end
+            close(h);
+        end
+        
+        function S = loadSubject(S,experiment,subject)
+            %loads all trials for a specific subject
+            %
+            %Example:
+            %   session.loadSubject(1);
+            %loads all the trials of the 1st subject
+            [~,~, y] = size(S.sessions);
+            for i=1:y
+                if ~isempty(S.sessions{experiment,subject,i})
+                    S.loadSubjectSession(experiment,subject,i);
+                end
+            end
+        end
+        function S = loadSubjectSession(S,experiment,subject,session)
+            %loads all trials for a specific session
+            %
+            %Example:
+            %   session.loadSubjectSession(1,2);
+            %loads the 2nd session of the 1st subject
+            %
+            switch(experiment)
+                case 1
+                    %Load Dataset I (SINGLE)
+                    load(S.sessions{experiment,subject,session});
+                    signal = eval('eeg');
+                    numTrials = length(S.trials) + 1;
+                    curTrials = S.split(signal,DIN_1,subject,session);
+                    for i=1:length(curTrials)
+                        S.trials{numTrials} = curTrials{i};
+                        numTrials = numTrials + 1;
+                    end
+                case 2
+                    %Load Dataset II (MULTI)
+                    load(S.sessions{experiment,subject,session});
+                    signal = eval('eeg');
+                    numTrials = length(S.trials) + 1;
+                    curTrials = S.split(signal,DIN_1,subject,session,labels);
+                    for i=1:length(curTrials)
+                        S.trials{numTrials} = curTrials{i};
+                        numTrials = numTrials + 1;
+                    end
+                case 3
+                    %Dataset III (EPOC-MULTI)
+                    SAMPLING_RATE = 128;
+                    load(strcat(S.sessions{experiment,subject,session},'i'));
+                    events = eval('events');
+                    marks = events(events(:,2)==32779,3);
+                    stops = events(events(:,2)==32780,3);
+                    numTrials = length(S.trials) + 1;
+                    labels = {4,2,3,5,1,2,5,4,2,3,1,5};
+                    for i=1:length(marks)
+                        signal = eeg(:,marks(i):stops(i) -1);
+                        label = labels{i};
+                        S.trials{numTrials} = eegtoolkit.util.Trial(signal,label,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.SSVEP);
+                        numTrials = numTrials + 1;
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                    end
+                    %load part 2
+                    load(strcat(S.sessions{experiment,subject,session},'ii'));
+                    events = eval('events');
+                    marks = events(events(:,2)==32779,3);
+                    stops = events(events(:,2)==32780,3);
+                    numTrials = length(S.trials) + 1;
+                    labels = {4,3,2,4,1,2,5,3,4,1,3,1,3};
+                    for i=1:length(marks)
+                        signal = eeg(:,marks(i):stops(i) -1);
+                        label = labels{i};
+                        S.trials{numTrials} = eegtoolkit.util.Trial(signal,label,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.SSVEP);
+                        numTrials = numTrials + 1;
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                    end
+                case 4
+                    %SCCN Dataset
+                    SAMPLING_RATE = 256;
+                    load(S.sessions{experiment,subject,session});
+                    [x,y,z,zz] = size(eeg);
+                    numTrials = length(S.trials) + 1;
+                    for i=1:x
+                        for j=1:zz
+                            S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(eeg(i,:,:,j)),i,SAMPLING_RATE,subject,j);
+                            numTrials = numTrials+1;
+                            S.subjectids = [S.subjectids subject];
+                            S.sessionids = [S.sessionids j];
+                        end
+                    end
+                case 5
+                    %ERRP Dataset
+                    SAMPLING_RATE = 256;
+                    %range of trial in milliseconds based on the stimulus
+                    %event
+                    range = [200,800];
+                    xstart = round(range(1)*SAMPLING_RATE/1000)-1500;
+                    xend = round(range(2)*SAMPLING_RATE/1000);
+                    load(S.sessions{experiment,subject,session});
+                    events = {'correct_movement', 'error_movement'};
+                    numTrials = length(S.trials) + 1;
+                    for ev=1:length(events)
+                        idxev = find(strcmp(EEG.events.name, events{ev}));
+                        epochs.(events{ev}) = zeros(length(xstart:xend), size(EEG.signal,2), length(idxev));
+                        for i=1:length(idxev)
+                            epochs.(events{ev})(:,:,i) = EEG.signal(EEG.events.position(idxev(i))+xstart:EEG.events.position(idxev(i))+xend,:);
+                        end
+                        GrandAverages.(events{ev}) = mean(epochs.(events{ev}),3);
+                    end
+                    [~,~,numCorrect] = size(epochs.correct_movement);
+                    [~,~,numError] = size(epochs.error_movement);
+                    for i=1:numCorrect
+                        S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(epochs.correct_movement(:,:,i))',1,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.ERRP);
+                        numTrials = numTrials + 1;
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                        
+                    end
+                    for i=1:numError
+                        S.trials{numTrials} = eegtoolkit.util.Trial(squeeze(epochs.error_movement(:,:,i))',2,SAMPLING_RATE,subject,session,eegtoolkit.util.Trial.ERRP);
+                        numTrials = numTrials + 1;
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                    end
+                case 6
+                    load(S.sessions{experiment,subject,session});
+                    [~,~,n] = size(x_train);
+                    numTrials = length(S.trials) + 1;
+                    for i=1:n
+                        signal = squeeze(x_train(:,:,i));
+                        label = y_train(i);
+                        S.trials{numTrials} = eegtoolkit.util.Trial(signal',label,128,1,1,eegtoolkit.util.Trial.MI);
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                        numTrials = numTrials + 1;
+                    end
+                case 7
+                    load(S.sessions{experiment,subject,session});
+                    [trialsegm,labels] = segmentGratzB(data{session},0.5,2.5,250);
+                    [n,~,~] = size(trialsegm);
+                    numTrials = length(S.trials) + 1;
+                    for i=1:n
+                        signal = squeeze(trialsegm(i,:,:));
+                        label = labels(i);
+                        S.trials{numTrials} = eegtoolkit.util.Trial(signal',label,250,subject,session,eegtoolkit.util.Trial.MI);
+                        S.subjectids = [S.subjectids subject];
+                        S.sessionids = [S.sessionids session];
+                        numTrials = numTrials + 1;
+                    end
+                otherwise
+                    error('invalid experiment id');
+            end
+        end
+        
+        function S = clearData(S)
+            %clears loaded data
+            S.trials = {};
+            S.subjectids = [];
+            S.sessionids = [];
+        end
+    end
+    
+    methods (Access = private)
+        function trials = split(S, signal, dins, subjectid, session,labels)
+            SAMPLING_RATE = 250;
+            timestamps = cell2mat(dins(2,:));
+            samples = cell2mat(dins(4,:));
+            [a numDins ]= size(dins);
+            sampleA= samples(1);
+            timeA = timestamps(1);
+            previous = timestamps(1);
+            ranges = [];
+            freqs = [];
+            times = [];
+            sum = 0;
+            count = 0;
+            i=2;
+            for i=2:numDins
+                current = timestamps(i);
+                if(current - previous) > S.THRESHOLD_SPLIT_MILLIS;
+                    sampleB = samples(i-1);
+                    timeB = timestamps(i-1);
+                    freqs = [freqs; (sum/count)];
+                    % don't ask why
+                    if(sampleB - sampleA>382)
+                        ranges = [ranges ; [sampleA (sampleA+1249)]];
+                        times = [times; [timeA timeB]];
+                    end
+                    sampleA = samples(i);
+                    timeA = timestamps(i);
+                    sum = 0;
+                    count = 0;
+                else
+                    sum = sum + (current-previous);
+                    count = count +1;
+                end
+                previous = timestamps(i);
+            end
+            %             if(isempty(labels))
+            sampleB = samples(i-1);
+            timeB = timestamps(i-1);
+            freqs = [freqs; (sum/count)];
+            ranges = [ranges; [sampleA sampleA+1249]];
+            times = [times; [timeA timeB]];
+            freqs = freqs*2;
+            freqs = 1000./freqs;
+            %             end
+            [numSplits a] = size(ranges);
+            trials = {};
+            i = 1;
+            for i=1:numSplits
+                if(nargin>5)
+                    trials{i} = eegtoolkit.util.Trial(signal(:, ranges(i,1):ranges(i,2)), labels{i},SAMPLING_RATE, subjectid,session,eegtoolkit.util.Trial.SSVEP);
+                    S.subjectids = [S.subjectids subjectid];
+                    S.sessionids = [S.sessionids session];
+                else
+                    trials{i} = eegtoolkit.util.Trial(signal(:,ranges(i,1):ranges(i,2)), freqs(i), SAMPLING_RATE, subjectid,session,eegtoolkit.util.Trial.SSVEP);
+                    S.subjectids = [S.subjectids subjectid];
+                    S.sessionids = [S.sessionids session];
+                end
+            end
+        end
+        
+        
+    end
+end
+
diff --git a/doc/+eegtoolkit/+util/@Session/graph.dot b/doc/+eegtoolkit/+util/@Session/graph.dot
new file mode 100644
index 0000000..3d285ba
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Session -> Session;
+
+  Session [URL="Session.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Session/graph.html b/doc/+eegtoolkit/+util/@Session/graph.html
new file mode 100644
index 0000000..f8dff3a
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@Session</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@Session">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@Session">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@Session</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@Session" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Session.html" title="Session" alt="" coords="105,29,102,22,95,15,84,10,70,7,55,5,39,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,39,52,55,53,70,52,84,49,95,43,102,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Session/graph.map b/doc/+eegtoolkit/+util/@Session/graph.map
new file mode 100644
index 0000000..921f312
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/graph.map
@@ -0,0 +1 @@
+<area shape="poly" id="node1" href="Session.html" title="Session" alt="" coords="105,29,102,22,95,15,84,10,70,7,55,5,39,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,39,52,55,53,70,52,84,49,95,43,102,37">
diff --git a/doc/+eegtoolkit/+util/@Session/graph.png b/doc/+eegtoolkit/+util/@Session/graph.png
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diff --git a/doc/+eegtoolkit/+util/@Session/index.html b/doc/+eegtoolkit/+util/@Session/index.html
new file mode 100644
index 0000000..6608428
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Session/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@Session</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@Session">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@Session">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@Session</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Session.html">Session</a></td><td>SESSION class </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/Trial.html b/doc/+eegtoolkit/+util/@Trial/Trial.html
new file mode 100644
index 0000000..5c35357
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Trial/Trial.html
@@ -0,0 +1,115 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of Trial</title>
+  <meta name="keywords" content="Trial">
+  <meta name="description" content="A class that defines a Trial">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@Trial</a> &gt; Trial.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>Trial
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>A class that defines a Trial</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> A class that defines a Trial
+ 
+ Properties:
+ signal: the signal of the trial, matrix m x n, where m is the channels
+ and n the samples
+ label: a label for the trial (typically assigned with the frequency that is calculated using DIN data)
+ duration: the duration of the trial in seconds
+ samplingRate: the samling rate used to capture the signal
+ subjectid: the subject from whom the trial was recorded
+ sessionid: the session id
+ type: the type of the trial. Supported types of trials:
+ SSVEP = 1;
+ ERRP = 2;
+ MI = 3;</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Trial.html" class="code" title="">Trial</a>	A class that defines a Trial</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="Trial.html" class="code" title="">Trial</a>	A class that defines a Trial</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function T = Trial(signal, label, samplingRate, subjectID, sessionID,type)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="Trial.m">Trial.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% A class that defines a Trial</span>
+0002 <span class="comment">%</span>
+0003 <span class="comment">% Properties:</span>
+0004 <span class="comment">% signal: the signal of the trial, matrix m x n, where m is the channels</span>
+0005 <span class="comment">% and n the samples</span>
+0006 <span class="comment">% label: a label for the trial (typically assigned with the frequency that is calculated using DIN data)</span>
+0007 <span class="comment">% duration: the duration of the trial in seconds</span>
+0008 <span class="comment">% samplingRate: the samling rate used to capture the signal</span>
+0009 <span class="comment">% subjectid: the subject from whom the trial was recorded</span>
+0010 <span class="comment">% sessionid: the session id</span>
+0011 <span class="comment">% type: the type of the trial. Supported types of trials:</span>
+0012 <span class="comment">% SSVEP = 1;</span>
+0013 <span class="comment">% ERRP = 2;</span>
+0014 <span class="comment">% MI = 3;</span>
+0015 
+0016 classdef <a href="Trial.html" class="code" title="">Trial</a> &lt; handle
+0017     
+0018     
+0019     properties (Constant)
+0020         <span class="comment">%Type of trial</span>
+0021         SSVEP = 1;
+0022         ERRP = 2;
+0023         MI = 3;
+0024     <span class="keyword">end</span>
+0025     
+0026     properties (Access = public)
+0027         signal; <span class="comment">% the signal of the trial</span>
+0028         label; <span class="comment">% a label for the trial (typically assigned with the frequency that is calculated using DIN data)</span>
+0029         duration; <span class="comment">% the duration of the trial in seconds</span>
+0030         samplingRate; <span class="comment">% the samling rate used to capture the signal</span>
+0031         subjectid; <span class="comment">%the subject from</span>
+0032         sessionid; <span class="comment">%the session id</span>
+0033         type;
+0034     <span class="keyword">end</span>
+0035     
+0036     methods (Access = public)
+0037         <a name="_sub0" href="#_subfunctions" class="code">function T = Trial(signal, label, samplingRate, subjectID, sessionID,type)</a>
+0038             T.signal = signal;
+0039             T.label = label;
+0040             T.samplingRate = samplingRate;
+0041             T.duration = length(signal)/samplingRate;
+0042             T.subjectid = subjectID;
+0043             T.sessionid = sessionID;
+0044             <span class="keyword">if</span> nargin&gt;5
+0045                 T.type = type;
+0046             <span class="keyword">end</span>
+0047         <span class="keyword">end</span>
+0048         
+0049     <span class="keyword">end</span>
+0050     
+0051 <span class="keyword">end</span>
+0052</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/Trial.m b/doc/+eegtoolkit/+util/@Trial/Trial.m
new file mode 100644
index 0000000..f3a4b06
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Trial/Trial.m
@@ -0,0 +1,52 @@
+% A class that defines a Trial
+% 
+% Properties:
+% signal: the signal of the trial, matrix m x n, where m is the channels
+% and n the samples
+% label: a label for the trial (typically assigned with the frequency that is calculated using DIN data)
+% duration: the duration of the trial in seconds
+% samplingRate: the samling rate used to capture the signal
+% subjectid: the subject from whom the trial was recorded
+% sessionid: the session id
+% type: the type of the trial. Supported types of trials:
+% SSVEP = 1;
+% ERRP = 2;
+% MI = 3;
+
+classdef Trial < handle
+    
+    
+    properties (Constant)
+        %Type of trial
+        SSVEP = 1;
+        ERRP = 2;
+        MI = 3;
+    end
+    
+    properties (Access = public)
+        signal; % the signal of the trial
+        label; % a label for the trial (typically assigned with the frequency that is calculated using DIN data)
+        duration; % the duration of the trial in seconds
+        samplingRate; % the samling rate used to capture the signal
+        subjectid; %the subject from
+        sessionid; %the session id
+        type;
+    end
+    
+    methods (Access = public)
+        function T = Trial(signal, label, samplingRate, subjectID, sessionID,type)
+            T.signal = signal;
+            T.label = label;
+            T.samplingRate = samplingRate;
+            T.duration = length(signal)/samplingRate;
+            T.subjectid = subjectID;
+            T.sessionid = sessionID;
+            if nargin>5
+                T.type = type;
+            end
+        end
+        
+    end
+    
+end
+
diff --git a/doc/+eegtoolkit/+util/@Trial/graph.dot b/doc/+eegtoolkit/+util/@Trial/graph.dot
new file mode 100644
index 0000000..f5d038e
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Trial/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  Trial -> Trial;
+
+  Trial [URL="Trial.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/graph.html b/doc/+eegtoolkit/+util/@Trial/graph.html
new file mode 100644
index 0000000..150af9a
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Trial/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for ./+eegtoolkit/+util/@Trial</title>
+  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@Trial">
+  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@Trial">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for ./+eegtoolkit/+util/@Trial</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@Trial" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="Trial.html" title="Trial" alt="" coords="79,29,77,22,71,15,63,10,53,7,41,5,30,7,19,10,11,15,6,22,4,29,6,37,11,43,19,49,30,52,41,53,53,52,63,49,71,43,77,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/graph.map b/doc/+eegtoolkit/+util/@Trial/graph.map
new file mode 100644
index 0000000..ec38555
--- /dev/null
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diff --git a/doc/+eegtoolkit/+util/@Trial/index.html b/doc/+eegtoolkit/+util/@Trial/index.html
new file mode 100644
index 0000000..0894d44
--- /dev/null
+++ b/doc/+eegtoolkit/+util/@Trial/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory ./+eegtoolkit/+util/@Trial</title>
+  <meta name="keywords" content="./+eegtoolkit/+util/@Trial">
+  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@Trial">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for ./+eegtoolkit/+util/@Trial</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="Trial.html">Trial</a></td><td>A class that defines a Trial </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
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diff --git a/doc/doxysearch.php b/doc/doxysearch.php
new file mode 100644
index 0000000..36112a4
--- /dev/null
+++ b/doc/doxysearch.php
@@ -0,0 +1,329 @@
+<?php
+/******************************************************************************
+ *
+ * $Id:$
+ *
+ * Copyright (C) 1997-2003 by Dimitri van Heesch.
+ *
+ * Permission to use, copy, modify, and distribute this software and its
+ * documentation under the terms of the GNU General Public License is hereby 
+ * granted. No representations are made about the suitability of this software 
+ * for any purpose. It is provided "as is" without express or implied warranty.
+ * See the GNU General Public License for more details.
+ *
+ */
+
+function readInt($file)
+{
+  $b1 = ord(fgetc($file)); $b2 = ord(fgetc($file));
+  $b3 = ord(fgetc($file)); $b4 = ord(fgetc($file));
+  return ($b1<<24)|($b2<<16)|($b3<<8)|$b4;
+}
+
+function readString($file)
+{
+  $result="";
+  while (ord($c=fgetc($file))) $result.=$c;
+  return $result;
+}
+
+function readHeader($file)
+{
+    $header =fgetc($file); $header.=fgetc($file);
+    $header.=fgetc($file); $header.=fgetc($file);
+    return $header;
+}
+
+function computeIndex($word)
+{
+  if (strlen($word)<2) return -1;
+  // high char of the index
+  $hi = ord($word{0});
+  if ($hi==0) return -1;
+  // low char of the index
+  $lo = ord($word{1});
+  if ($lo==0) return -1;
+  // return index
+  return $hi*256+$lo;
+}
+
+function search($file,$word,&$statsList)
+{
+  $index = computeIndex($word);
+  if ($index!=-1) // found a valid index
+  {
+    fseek($file,$index*4+4); // 4 bytes per entry, skip header
+    $index = readInt($file);
+    if ($index) // found words matching first two characters
+    {
+      $start=sizeof($statsList);
+      $count=$start;
+      fseek($file,$index);
+      $w = readString($file);
+      while ($w)
+      {
+        $statIdx = readInt($file);
+        if ($word==substr($w,0,strlen($word)))
+        { // found word that matches (as substring)
+          $statsList[$count++]=array(
+              "word"=>$word,
+              "match"=>$w,
+              "index"=>$statIdx,
+              "full"=>strlen($w)==strlen($word),
+              "docs"=>array()
+              );
+        }
+        $w = readString($file);
+      }
+      $totalFreq=0;
+      for ($count=$start;$count<sizeof($statsList);$count++)
+      {
+        $statInfo = &$statsList[$count];
+        fseek($file,$statInfo["index"]); 
+        $numDocs = readInt($file);
+        $docInfo = array();
+        // read docs info + occurrence frequency of the word
+        for ($i=0;$i<$numDocs;$i++)
+        {
+          $idx=readInt($file); 
+          $freq=readInt($file); 
+          $docInfo[$i]=array("idx"=>$idx,"freq"=>$freq,"rank"=>0.0);
+          $totalFreq+=$freq;
+          if ($statInfo["full"]) $totalfreq+=$freq;
+        }
+        // read name an url info for the doc
+        for ($i=0;$i<$numDocs;$i++)
+        {
+          fseek($file,$docInfo[$i]["idx"]);
+          $docInfo[$i]["name"]=readString($file);
+          $docInfo[$i]["url"]=readString($file);
+        }
+        $statInfo["docs"]=$docInfo;
+      }
+      for ($count=$start;$count<sizeof($statsList);$count++)
+      {
+        $statInfo = &$statsList[$count];
+        for ($i=0;$i<sizeof($statInfo["docs"]);$i++)
+        {
+          $docInfo = &$statInfo["docs"];
+          // compute frequency rank of the word in each doc
+          $statInfo["docs"][$i]["rank"]=
+            (float)$docInfo[$i]["freq"]/$totalFreq;
+        }
+      }
+    }
+  }
+  return $statsList;
+}
+
+function combine_results($results,&$docs)
+{
+  foreach ($results as $wordInfo)
+  {
+    $docsList = &$wordInfo["docs"];
+    foreach ($docsList as $di)
+    {
+      $key=$di["url"];
+      $rank=$di["rank"];
+      if (in_array($key, array_keys($docs)))
+      {
+        $docs[$key]["rank"]+=$rank;
+        $docs[$key]["rank"]*=2; // multiple matches increases rank 
+      }
+      else
+      {
+        $docs[$key] = array("url"=>$key,
+            "name"=>$di["name"],
+            "rank"=>$rank
+            );
+      }
+      $docs[$key]["words"][] = array(
+               "word"=>$wordInfo["word"],
+               "match"=>$wordInfo["match"],
+               "freq"=>$di["freq"]
+               );
+    }
+  }
+  return $docs;
+}
+
+function normalize_ranking(&$docs)
+{
+  $maxRank = 0.0000001;
+  // compute maximal rank
+  foreach ($docs as $doc) 
+  {
+    if ($doc["rank"]>$maxRank)
+    {
+      $maxRank=$doc["rank"];
+    }
+  }
+  reset($docs);
+  // normalize rankings
+  while (list ($key, $val) = each ($docs)) 
+  {
+    $docs[$key]["rank"]*=100/$maxRank;
+  }
+}
+
+function filter_results($docs,&$requiredWords,&$forbiddenWords)
+{
+  $filteredDocs=array();
+  while (list ($key, $val) = each ($docs)) 
+  {
+    $words = &$docs[$key]["words"];
+    $copy=1; // copy entry by default
+    if (sizeof($requiredWords)>0)
+    {
+      foreach ($requiredWords as $reqWord)
+      {
+        $found=0;
+        foreach ($words as $wordInfo)
+        { 
+          $found = $wordInfo["word"]==$reqWord;
+          if ($found) break;
+        }
+        if (!$found) 
+        {
+          $copy=0; // document contains none of the required words
+          break;
+        }
+      }
+    }
+    if (sizeof($forbiddenWords)>0)
+    {
+      foreach ($words as $wordInfo)
+      {
+        if (in_array($wordInfo["word"],$forbiddenWords))
+        {
+          $copy=0; // document contains a forbidden word
+          break;
+        }
+      }
+    }
+    if ($copy) $filteredDocs[$key]=$docs[$key];
+  }
+  return $filteredDocs;
+}
+
+function compare_rank($a,$b)
+{
+  return ($a["rank"]>$b["rank"]) ? -1 : 1; 
+}
+
+function sort_results($docs,&$sorted)
+{
+  $sorted = $docs;
+  usort($sorted,"compare_rank");
+  return $sorted;
+}
+
+function report_results(&$docs)
+{
+  echo "<table cellspacing=\"2\">\n";
+  echo "  <tr>\n";
+  echo "    <td colspan=\"2\"><h2>Search Results</h2></td>\n";
+  echo "  </tr>\n";
+  $numDocs = sizeof($docs);
+  if ($numDocs==0)
+  {
+    echo "  <tr>\n";
+    echo "    <td colspan=\"2\">".matches_text(0)."</td>\n";
+    echo "  </tr>\n";
+  }
+  else
+  {
+    echo "  <tr>\n";
+    echo "    <td colspan=\"2\">".matches_text($numDocs);
+    echo "\n";
+    echo "    </td>\n";
+    echo "  </tr>\n";
+    $num=1;
+    foreach ($docs as $doc)
+    {
+      echo "  <tr>\n";
+      echo "    <td align=\"right\">$num.</td>";
+      echo     "<td><a class=\"el\" href=\"".$doc["url"]."\">".$doc["name"]."</a></td>\n";
+      echo "  <tr>\n";
+      echo "    <td></td><td class=\"tiny\">Matches: ";
+      foreach ($doc["words"] as $wordInfo)
+      {
+        $word = $wordInfo["word"];
+        $matchRight = substr($wordInfo["match"],strlen($word));
+        echo "<b>$word</b>$matchRight(".$wordInfo["freq"].") ";
+      }
+      echo "    </td>\n";
+      echo "  </tr>\n";
+      $num++;
+    }
+  }
+  echo "</table>\n";
+}
+
+function matches_text($num)
+{
+  if ($num==0)
+  {
+    return 'Sorry, no documents matching your query.';
+  }
+  else if ($num==1)
+  {
+    return 'Found 1 document matching your query.';
+  }
+  else // $num>1
+  {
+    return 'Found '.$num.' documents matching your query. Showing best matches first.';
+  }
+}
+
+function main($idxfile)
+{
+  if(strcmp('4.1.0', phpversion()) > 0) 
+  {
+    die("Error: PHP version 4.1.0 or above required!");
+  }
+  if (!($file=fopen($idxfile,"rb"))) 
+  {
+    die("Error: Search index file could NOT be opened!");
+  }
+  if (readHeader($file)!="DOXS")
+  {
+    die("Error: Header of index file is invalid!");
+  }
+  $query="";
+  if (array_key_exists("query", $_GET))
+  {
+    $query=$_GET["query"];
+  }
+  $results = array();
+  $requiredWords = array();
+  $forbiddenWords = array();
+  $foundWords = array();
+  $word=strtolower(strtok($query," "));
+  while ($word) // for each word in the search query
+  {
+    if (($word{0}=='+')) { $word=substr($word,1); $requiredWords[]=$word; }
+    if (($word{0}=='-')) { $word=substr($word,1); $forbiddenWords[]=$word; }
+    if (!in_array($word,$foundWords))
+    {
+      $foundWords[]=$word;
+      search($file,$word,$results);
+    }
+    $word=strtolower(strtok(" "));
+  }
+  $docs = array();
+  combine_results($results,$docs);
+  // filter out documents with forbidden word or that do not contain
+  // required words
+  $filteredDocs = filter_results($docs,$requiredWords,$forbiddenWords);
+  // normalize rankings so they are in the range [0-100]
+  normalize_ranking($filteredDocs);
+  // sort the results based on rank
+  $sorted = array();
+  sort_results($filteredDocs,$sorted);
+  // report results to the user
+  report_results($sorted);
+  fclose($file);
+}
+
+?>
diff --git a/doc/exampleCSP.html b/doc/exampleCSP.html
new file mode 100644
index 0000000..b25686a
--- /dev/null
+++ b/doc/exampleCSP.html
@@ -0,0 +1,87 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleCSP</title>
+  <meta name="keywords" content="exampleCSP">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleCSP.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleCSP
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleCSP.m">exampleCSP.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 sess = eegtoolkit.util.Session;
+0002 sess.loadAll(6);
+0003 <span class="comment">%</span>
+0004 
+0005 <span class="comment">% load('testingMotorVag1');</span>
+0006 <span class="comment">% % load</span>
+0007 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0008 <span class="comment">% % sess.loadMOTOR(labels,trials);</span>
+0009 <span class="comment">% sess.loadVag(trials,labels);</span>
+0010 
+0011 ss = eegtoolkit.preprocessing.SampleSelection;
+0012 ss.channels = [1,3];
+0013 ss.sampleRange = [384,896];
+0014 
+0015 [z,p,k]=butter(3,[8,16]/64);
+0016 [s,g]=zp2sos(z,p,k);
+0017 Hd = dfilt.df2sos(s,g);
+0018 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">%</span>
+0019 df.filt = Hd;
+0020 
+0021 refer = eegtoolkit.preprocessing.Rereferencing;
+0022 refer.meanSignal = 1;
+0023 
+0024 extr = eegtoolkit.featextraction.RawSignal;
+0025 
+0026 classif = eegtoolkit.classification.CSPWrapper;
+0027 classif.baseClassifier = eegtoolkit.classification.LIBSVM;
+0028 
+0029 experiment = eegtoolkit.experiment.Experimenter;
+0030 experiment.session = sess;
+0031 experiment.preprocessing = {ss,refer,df};
+0032 experiment.featextraction = extr;
+0033 experiment.classification = classif;
+0034 experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+0035 <span class="comment">% experiment.run();</span>
+0036 <span class="comment">% experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;</span>
+0037 experiment.run(3);
+0038 accuracy = experiment.results{1}.getAccuracy();
+0039</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleCSP.m b/doc/exampleCSP.m
new file mode 100644
index 0000000..4c466b6
--- /dev/null
+++ b/doc/exampleCSP.m
@@ -0,0 +1,39 @@
+sess = eegtoolkit.util.Session;
+sess.loadAll(6);
+% 
+
+% load('testingMotorVag1');
+% % load
+% sess = eegtoolkit.util.Session;
+% % sess.loadMOTOR(labels,trials);
+% sess.loadVag(trials,labels);
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.channels = [1,3];
+ss.sampleRange = [384,896];
+
+[z,p,k]=butter(3,[8,16]/64);
+[s,g]=zp2sos(z,p,k);
+Hd = dfilt.df2sos(s,g);
+df = eegtoolkit.preprocessing.DigitalFilter; %
+df.filt = Hd;
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+refer.meanSignal = 1;
+
+extr = eegtoolkit.featextraction.RawSignal;
+
+classif = eegtoolkit.classification.CSPWrapper;
+classif.baseClassifier = eegtoolkit.classification.LIBSVM;
+
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {ss,refer,df};
+experiment.featextraction = extr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+% experiment.run();
+% experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+experiment.run(3);
+accuracy = experiment.results{1}.getAccuracy();
+
diff --git a/doc/exampleCombiCCA.html b/doc/exampleCombiCCA.html
new file mode 100644
index 0000000..a939c0d
--- /dev/null
+++ b/doc/exampleCombiCCA.html
@@ -0,0 +1,93 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleCombiCCA</title>
+  <meta name="keywords" content="exampleCombiCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleCombiCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleCombiCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleCombiCCA.m">exampleCombiCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 m_secs = 0.5:0.5:4;
+0002 <span class="keyword">for</span> ii=1:8
+0003     <span class="keyword">for</span> jj = 1:8
+0004         sess = eegtoolkit.util.Session;
+0005         <span class="comment">% sess.loadAll(4);</span>
+0006         <span class="comment">% sess.loadAll(4);</span>
+0007         sess.loadSubject(4,ii);
+0008         
+0009         ss = eegtoolkit.preprocessing.SampleSelection;
+0010         ss.channels = 1:8;
+0011         <span class="comment">% ss.sampleRange = [75,1024+74];</span>
+0012         ss.sampleRange = [75,74+256*m_secs(jj)];
+0013         <span class="comment">% ss.sampleRange = [1,1140];</span>
+0014         <span class="comment">% 75:1024+74</span>
+0015         [z,p,k]=butter(3,[6,80]/128);
+0016         [s,g]=zp2sos(z,p,k);
+0017         Hd = dfilt.df2sos(s,g);
+0018         df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">%</span>
+0019         df.filt = Hd;
+0020         
+0021         refer = eegtoolkit.preprocessing.Rereferencing;
+0022         refer.meanSignal = 1;
+0023         
+0024         extr = eegtoolkit.featextraction.RawSignal;
+0025         sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];
+0026         classif = eegtoolkit.classification.CombiCCA(sti_f,4,256*m_secs(jj),256);
+0027         classif.baseClassifier = eegtoolkit.classification.MaxChooser;
+0028         
+0029         experiment = eegtoolkit.experiment.Experimenter;
+0030         experiment.session = sess;
+0031         experiment.preprocessing = {ss,refer,df};
+0032         experiment.featextraction = extr;
+0033         experiment.classification = classif;
+0034         <span class="comment">% experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;</span>
+0035         <span class="comment">% experiment.run();</span>
+0036         experiment.evalMethod = experiment.EVAL_METHOD_LOBO;
+0037         experiment.run();
+0038         <span class="keyword">for</span> i=1:length(experiment.results)
+0039             accuracy(i) = experiment.results{i}.getAccuracy();
+0040         <span class="keyword">end</span>
+0041         acc2(ii,jj) = mean(accuracy);
+0042         
+0043         <span class="comment">% accuracy = experiment.results{1}.getAccuracy();</span>
+0044     <span class="keyword">end</span>
+0045 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleCombiCCA.m b/doc/exampleCombiCCA.m
new file mode 100644
index 0000000..f54f361
--- /dev/null
+++ b/doc/exampleCombiCCA.m
@@ -0,0 +1,45 @@
+m_secs = 0.5:0.5:4;
+for ii=1:8
+    for jj = 1:8
+        sess = eegtoolkit.util.Session;
+        % sess.loadAll(4);
+        % sess.loadAll(4);
+        sess.loadSubject(4,ii);
+        
+        ss = eegtoolkit.preprocessing.SampleSelection;
+        ss.channels = 1:8;
+        % ss.sampleRange = [75,1024+74];
+        ss.sampleRange = [75,74+256*m_secs(jj)];
+        % ss.sampleRange = [1,1140];
+        % 75:1024+74
+        [z,p,k]=butter(3,[6,80]/128);
+        [s,g]=zp2sos(z,p,k);
+        Hd = dfilt.df2sos(s,g);
+        df = eegtoolkit.preprocessing.DigitalFilter; %
+        df.filt = Hd;
+        
+        refer = eegtoolkit.preprocessing.Rereferencing;
+        refer.meanSignal = 1;
+        
+        extr = eegtoolkit.featextraction.RawSignal;
+        sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];
+        classif = eegtoolkit.classification.CombiCCA(sti_f,4,256*m_secs(jj),256);
+        classif.baseClassifier = eegtoolkit.classification.MaxChooser;
+        
+        experiment = eegtoolkit.experiment.Experimenter;
+        experiment.session = sess;
+        experiment.preprocessing = {ss,refer,df};
+        experiment.featextraction = extr;
+        experiment.classification = classif;
+        % experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+        % experiment.run();
+        experiment.evalMethod = experiment.EVAL_METHOD_LOBO;
+        experiment.run();
+        for i=1:length(experiment.results)
+            accuracy(i) = experiment.results{i}.getAccuracy();
+        end
+        acc2(ii,jj) = mean(accuracy);
+        
+        % accuracy = experiment.results{1}.getAccuracy();
+    end
+end
diff --git a/doc/exampleDefault.html b/doc/exampleDefault.html
new file mode 100644
index 0000000..46b5f13
--- /dev/null
+++ b/doc/exampleDefault.html
@@ -0,0 +1,97 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleDefault</title>
+  <meta name="keywords" content="exampleDefault">
+  <meta name="description" content="Load the data. Call this once outside of the script so you dont have to">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleDefault.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleDefault
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Load the data. Call this once outside of the script so you dont have to</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(1); %Loads dataset I</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleDefault.m">exampleDefault.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0002 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0003 <span class="comment">% Matlab path</span>
+0004 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0005 <span class="comment">% sess.loadAll(1); %Loads dataset I</span>
+0006 
+0007 <span class="comment">%Load a filter from the samples</span>
+0008 load filters/filt_IIRElliptic.mat;
+0009 
+0010 <span class="comment">%Extract features with the pwelch method</span>
+0011 extr = eegtoolkit.featextraction.PWelch;
+0012 
+0013 refer = eegtoolkit.preprocessing.Rereferencing;
+0014 <span class="comment">%Subtract the mean from the signal</span>
+0015 refer.meanSignal = 1;
+0016 
+0017 ss = eegtoolkit.preprocessing.SampleSelection;
+0018 ss.sampleRange = [1,1250]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0019 ss.channels = 126; <span class="comment">% Specify the channel(s) to be used</span>
+0020 
+0021 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0022 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0023 
+0024 <span class="comment">%Configure the classifier</span>
+0025 classif = eegtoolkit.classification.LIBSVMFast;
+0026 
+0027 <span class="comment">%Set the Experimenter wrapper class</span>
+0028 experiment = eegtoolkit.experiment.Experimenter;
+0029 experiment.session = sess;
+0030 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0031 experiment.preprocessing = {ss,refer,df};
+0032 experiment.featextraction = extr;
+0033 experiment.classification = classif;
+0034 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0035 experiment.run();
+0036 <span class="keyword">for</span> i=1:length(experiment.results)
+0037     accuracies(i) = experiment.results{i}.getAccuracy();
+0038 <span class="keyword">end</span>
+0039 
+0040 accuracies'
+0041 <span class="comment">%mean accuracy for all subjects</span>
+0042 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0043 <span class="comment">%get the configuration used (for reporting)</span>
+0044 experiment.getExperimentInfo
+0045 experiment.getTime</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleDefault.m b/doc/exampleDefault.m
new file mode 100644
index 0000000..82ea4d4
--- /dev/null
+++ b/doc/exampleDefault.m
@@ -0,0 +1,45 @@
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(1); %Loads dataset I
+
+%Load a filter from the samples
+load filters/filt_IIRElliptic.mat;
+
+%Extract features with the pwelch method
+extr = eegtoolkit.featextraction.PWelch;
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [1,1250]; % Specify the sample range to be used for each Trial
+ss.channels = 126; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+%Configure the classifier
+classif = eegtoolkit.classification.LIBSVMFast;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {ss,refer,df};
+experiment.featextraction = extr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+experiment.getExperimentInfo
+experiment.getTime
diff --git a/doc/exampleEPOCCCASVM.html b/doc/exampleEPOCCCASVM.html
new file mode 100644
index 0000000..45f41a8
--- /dev/null
+++ b/doc/exampleEPOCCCASVM.html
@@ -0,0 +1,105 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleEPOCCCASVM</title>
+  <meta name="keywords" content="exampleEPOCCCASVM">
+  <meta name="description" content="Load the data. Call this once outside of the script so you dont have to">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleEPOCCCASVM.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleEPOCCCASVM
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Load the data. Call this once outside of the script so you dont have to</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(3); %its best to do this once, outside the script (too much
+ time)</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleEPOCCCASVM.m">exampleEPOCCCASVM.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0002 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0003 <span class="comment">% Matlab path</span>
+0004 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0005 <span class="comment">% sess.loadAll(3); %its best to do this once, outside the script (too much</span>
+0006 <span class="comment">% time)</span>
+0007 
+0008 <span class="comment">%Load a filter from the samples</span>
+0009 load filters/epocfilter;
+0010 <span class="comment">% 7 = O1</span>
+0011 <span class="comment">% 8 = O2</span>
+0012 
+0013 <span class="comment">% Stimulus frequencies for generating the CCA reference signals</span>
+0014 sti_f = [12,10,8.57,7.5,6.66];
+0015 
+0016 <span class="comment">% CCA feat extraction method</span>
+0017 extr = eegtoolkit.featextraction.CCA(sti_f,1:4,128,4);
+0018 extr.allFeatures = 1;
+0019 
+0020 refer = eegtoolkit.preprocessing.Rereferencing;
+0021 <span class="comment">%Subtract the mean from the signal</span>
+0022 refer.meanSignal = 1;
+0023 
+0024 ss = eegtoolkit.preprocessing.SampleSelection;
+0025 ss.sampleRange = [64,640]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0026 ss.channels = 6:9; <span class="comment">% Specify the channel(s) to be used</span>
+0027 
+0028 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0029 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0030 
+0031 <span class="comment">%Configure the classifier</span>
+0032 classif = eegtoolkit.classification.LIBSVM;
+0033 
+0034 <span class="comment">%Set the Experimenter wrapper class</span>
+0035 experiment = eegtoolkit.experiment.Experimenter;
+0036 experiment.session = sess;
+0037 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0038 experiment.preprocessing = {ss,df};
+0039 experiment.featextraction = extr;
+0040 experiment.classification = classif;
+0041 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0042 experiment.run();
+0043 <span class="keyword">for</span> i=1:length(experiment.results)
+0044     accuracies(i) = experiment.results{i}.getAccuracy();
+0045 <span class="keyword">end</span>
+0046 
+0047 accuracies'
+0048 <span class="comment">%mean accuracy for all subjects</span>
+0049 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0050 <span class="comment">%get the configuration used (for reporting)</span>
+0051 <span class="comment">% experiment.getExperimentInfo</span>
+0052 <span class="comment">% experiment.getTime</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleEPOCCCASVM.m b/doc/exampleEPOCCCASVM.m
new file mode 100644
index 0000000..cc2e828
--- /dev/null
+++ b/doc/exampleEPOCCCASVM.m
@@ -0,0 +1,52 @@
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(3); %its best to do this once, outside the script (too much
+% time)
+
+%Load a filter from the samples
+load filters/epocfilter;
+% 7 = O1
+% 8 = O2
+
+% Stimulus frequencies for generating the CCA reference signals
+sti_f = [12,10,8.57,7.5,6.66];
+
+% CCA feat extraction method
+extr = eegtoolkit.featextraction.CCA(sti_f,1:4,128,4);
+extr.allFeatures = 1;
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [64,640]; % Specify the sample range to be used for each Trial
+ss.channels = 6:9; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+%Configure the classifier
+classif = eegtoolkit.classification.LIBSVM;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {ss,df};
+experiment.featextraction = extr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+% experiment.getExperimentInfo
+% experiment.getTime
\ No newline at end of file
diff --git a/doc/exampleERRP.html b/doc/exampleERRP.html
new file mode 100644
index 0000000..80d30c3
--- /dev/null
+++ b/doc/exampleERRP.html
@@ -0,0 +1,91 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleERRP</title>
+  <meta name="keywords" content="exampleERRP">
+  <meta name="description" content="d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleERRP.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleERRP
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleERRP.m">exampleERRP.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</span>
+0002 
+0003 sess = eegtoolkit.util.Session;
+0004 sess.loadSubject(5,6);
+0005 
+0006 [z,p,k]=butter(3,[6,40]/128);
+0007 [s,g]=zp2sos(z,p,k);
+0008 Hd = dfilt.df2sos(s,g);
+0009 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">%</span>
+0010 df.filt = Hd;
+0011 
+0012 ss = eegtoolkit.preprocessing.SampleSelection;
+0013 ss.channels = [4,9,14];
+0014 ss.sampleRange = 1500:1:1655;
+0015 
+0016 extr = {};
+0017 <span class="keyword">for</span> i=1:3
+0018     extr{i} = eegtoolkit.featextraction.ERRPFeatures;
+0019     extr{i}.channel = 1;
+0020 <span class="keyword">end</span>
+0021 
+0022 aggr = eegtoolkit.aggregation.ChannelConcat;
+0023 
+0024 classif = eegtoolkit.classification.LIBSVM;
+0025 
+0026 <span class="comment">%Setup experiment</span>
+0027 experiment = eegtoolkit.experiment.Experimenter;
+0028 experiment.session = sess;
+0029 experiment.preprocessing = {df,ss};
+0030 experiment.featextraction = extr;
+0031 experiment.aggregator = aggr;
+0032 experiment.classification = classif;
+0033 experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+0034 
+0035 experiment.run(10);
+0036 
+0037 accuracies = [];
+0038 <span class="keyword">for</span> i=1:length(experiment.results)
+0039     accuracies(i) = experiment.results{i}.getAccuracy();
+0040 <span class="keyword">end</span>
+0041 
+0042 accuracies'
+0043 fprintf(<span class="string">'mean acc = %.2f\n'</span>,mean(accuracies));</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleERRP.m b/doc/exampleERRP.m
new file mode 100644
index 0000000..2723761
--- /dev/null
+++ b/doc/exampleERRP.m
@@ -0,0 +1,43 @@
+% d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');
+
+sess = eegtoolkit.util.Session;
+sess.loadSubject(5,6);
+
+[z,p,k]=butter(3,[6,40]/128);
+[s,g]=zp2sos(z,p,k);
+Hd = dfilt.df2sos(s,g);
+df = eegtoolkit.preprocessing.DigitalFilter; %
+df.filt = Hd;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.channels = [4,9,14];
+ss.sampleRange = 1500:1:1655;
+
+extr = {};
+for i=1:3
+    extr{i} = eegtoolkit.featextraction.ERRPFeatures;
+    extr{i}.channel = 1;
+end
+
+aggr = eegtoolkit.aggregation.ChannelConcat;
+
+classif = eegtoolkit.classification.LIBSVM;
+
+%Setup experiment
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {df,ss};
+experiment.featextraction = extr;
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+
+experiment.run(10);
+
+accuracies = [];
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+fprintf('mean acc = %.2f\n',mean(accuracies));
\ No newline at end of file
diff --git a/doc/exampleEarlyFusion.html b/doc/exampleEarlyFusion.html
new file mode 100644
index 0000000..2ac0e86
--- /dev/null
+++ b/doc/exampleEarlyFusion.html
@@ -0,0 +1,123 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleEarlyFusion</title>
+  <meta name="keywords" content="exampleEarlyFusion">
+  <meta name="description" content="Leave one subject out testing">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleEarlyFusion.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleEarlyFusion
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Leave one subject out testing</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Leave one subject out testing
+ load filtMAMEM; % load a filter
+ sess = eegtoolkit.util.Session(Hhp);
+ sess.loadAll(1); %its best to do this once, outside the script (too much
+ time)
+ transf = eegtoolkit.transformer.PWelchTransformer();
+ Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(1); %Loads dataset I</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleEarlyFusion.m">exampleEarlyFusion.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Leave one subject out testing</span>
+0002 <span class="comment">% load filtMAMEM; % load a filter</span>
+0003 <span class="comment">% sess = eegtoolkit.util.Session(Hhp);</span>
+0004 <span class="comment">% sess.loadAll(1); %its best to do this once, outside the script (too much</span>
+0005 <span class="comment">% time)</span>
+0006 <span class="comment">% transf = eegtoolkit.transformer.PWelchTransformer();</span>
+0007 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0008 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0009 <span class="comment">% Matlab path</span>
+0010 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0011 <span class="comment">% sess.loadAll(1); %Loads dataset I</span>
+0012 
+0013 <span class="comment">%Load a filter from the samples</span>
+0014 load filters/filt_IIRElliptic;
+0015 
+0016 
+0017 
+0018 refer = eegtoolkit.preprocessing.Rereferencing;
+0019 <span class="comment">%Subtract the mean from the signal</span>
+0020 refer.meanSignal = 1;
+0021 
+0022 ss = eegtoolkit.preprocessing.SampleSelection;
+0023 ss.sampleRange = [1,1250]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0024 ss.channels = [138,139,150]; <span class="comment">% Specify the channel(s) to be used</span>
+0025 
+0026 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0027 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0028 
+0029 
+0030 <span class="comment">%Extract features with the pwelch method</span>
+0031 extr1 = eegtoolkit.featextraction.PWelch;
+0032 extr1.channel = 1; <span class="comment">%will use channel 138</span>
+0033 
+0034 extr2 = eegtoolkit.featextraction.PWelch;
+0035 extr2.channel = 2; <span class="comment">%will use channel 139</span>
+0036 
+0037 extr3 = eegtoolkit.featextraction.PWelch;
+0038 extr3.channel = 3; <span class="comment">%will use channel 150</span>
+0039 
+0040 extr = {extr1,extr2,extr3};
+0041 <span class="comment">% Average all three channels so as to get a new feature vector</span>
+0042 aggr = eegtoolkit.aggregation.ChannelAveraging;
+0043 <span class="comment">%Configure the classifier</span>
+0044 classif = eegtoolkit.classification.LIBSVM;
+0045 
+0046 <span class="comment">%Set the Experimenter wrapper class</span>
+0047 experiment = eegtoolkit.experiment.Experimenter;
+0048 experiment.session = sess;
+0049 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0050 experiment.preprocessing = {ss,refer,df};
+0051 experiment.featextraction = {extr1,extr2,extr3};
+0052 experiment.aggregator = aggr;
+0053 experiment.classification = classif;
+0054 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0055 experiment.run();
+0056 <span class="keyword">for</span> i=1:length(experiment.results)
+0057     accuracies(i) = experiment.results{i}.getAccuracy();
+0058 <span class="keyword">end</span>
+0059 
+0060 accuracies'
+0061 <span class="comment">%mean accuracy for all subjects</span>
+0062 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0063 <span class="comment">%get the configuration used (for reporting)</span>
+0064 experiment.getExperimentInfo
+0065 experiment.getTime</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleEarlyFusion.m b/doc/exampleEarlyFusion.m
new file mode 100644
index 0000000..e3e79b4
--- /dev/null
+++ b/doc/exampleEarlyFusion.m
@@ -0,0 +1,65 @@
+% Leave one subject out testing
+% load filtMAMEM; % load a filter
+% sess = eegtoolkit.util.Session(Hhp);
+% sess.loadAll(1); %its best to do this once, outside the script (too much
+% time)
+% transf = eegtoolkit.transformer.PWelchTransformer();
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(1); %Loads dataset I
+
+%Load a filter from the samples
+load filters/filt_IIRElliptic;
+
+
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [1,1250]; % Specify the sample range to be used for each Trial
+ss.channels = [138,139,150]; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+
+%Extract features with the pwelch method
+extr1 = eegtoolkit.featextraction.PWelch;
+extr1.channel = 1; %will use channel 138
+
+extr2 = eegtoolkit.featextraction.PWelch;
+extr2.channel = 2; %will use channel 139
+
+extr3 = eegtoolkit.featextraction.PWelch;
+extr3.channel = 3; %will use channel 150
+
+extr = {extr1,extr2,extr3};
+% Average all three channels so as to get a new feature vector
+aggr = eegtoolkit.aggregation.ChannelAveraging;
+%Configure the classifier
+classif = eegtoolkit.classification.LIBSVM;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {ss,refer,df};
+experiment.featextraction = {extr1,extr2,extr3};
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+experiment.getExperimentInfo
+experiment.getTime
\ No newline at end of file
diff --git a/doc/exampleEpoc.html b/doc/exampleEpoc.html
new file mode 100644
index 0000000..de952b2
--- /dev/null
+++ b/doc/exampleEpoc.html
@@ -0,0 +1,106 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleEpoc</title>
+  <meta name="keywords" content="exampleEpoc">
+  <meta name="description" content="Load the data. Call this once outside of the script so you dont have to">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleEpoc.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleEpoc
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Load the data. Call this once outside of the script so you dont have to</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(3); %its best to do this once, outside the script (too much
+ time)</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleEpoc.m">exampleEpoc.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0002 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0003 <span class="comment">% Matlab path</span>
+0004 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0005 <span class="comment">% sess.loadAll(3); %its best to do this once, outside the script (too much</span>
+0006 <span class="comment">% time)</span>
+0007 
+0008 <span class="comment">%Load a filter from the samples</span>
+0009 load filters/epocfilter;
+0010 <span class="comment">% 7 = O1</span>
+0011 <span class="comment">% 8 = O2</span>
+0012 
+0013 <span class="comment">% Stimulus frequencies. The order corresponds to the label id (12Hz=1,</span>
+0014 <span class="comment">% 10Hz=2, 8.57Hz=3, 7.5Hz=4, 6.66Hz=5)</span>
+0015 <span class="comment">% If the order is wrong, then the &quot;Max&quot; classifier will not work properly</span>
+0016 sti_f = [12,10,8.57,7.5,6.66];
+0017 
+0018 <span class="comment">% CCA feat extraction method</span>
+0019 extr = eegtoolkit.featextraction.CCA(sti_f,1:4,128,4);
+0020 
+0021 refer = eegtoolkit.preprocessing.Rereferencing;
+0022 <span class="comment">%Subtract the mean from the signal</span>
+0023 refer.meanSignal = 1;
+0024 
+0025 ss = eegtoolkit.preprocessing.SampleSelection;
+0026 ss.sampleRange = [64,640]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0027 ss.channels = 6:9; <span class="comment">% Specify the channel(s) to be used</span>
+0028 
+0029 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0030 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0031 
+0032 <span class="comment">%Configure the classifier</span>
+0033 classif = eegtoolkit.classification.MaxChooser;
+0034 
+0035 <span class="comment">%Set the Experimenter wrapper class</span>
+0036 experiment = eegtoolkit.experiment.Experimenter;
+0037 experiment.session = sess;
+0038 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0039 experiment.preprocessing = {ss,df};
+0040 experiment.featextraction = extr;
+0041 experiment.classification = classif;
+0042 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0043 experiment.run();
+0044 <span class="keyword">for</span> i=1:length(experiment.results)
+0045     accuracies(i) = experiment.results{i}.getAccuracy();
+0046 <span class="keyword">end</span>
+0047 
+0048 accuracies'
+0049 <span class="comment">%mean accuracy for all subjects</span>
+0050 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0051 <span class="comment">%get the configuration used (for reporting)</span>
+0052 <span class="comment">% experiment.getExperimentInfo</span>
+0053 <span class="comment">% experiment.getTime</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleEpoc.m b/doc/exampleEpoc.m
new file mode 100644
index 0000000..dc55bb7
--- /dev/null
+++ b/doc/exampleEpoc.m
@@ -0,0 +1,53 @@
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(3); %its best to do this once, outside the script (too much
+% time)
+
+%Load a filter from the samples
+load filters/epocfilter;
+% 7 = O1
+% 8 = O2
+
+% Stimulus frequencies. The order corresponds to the label id (12Hz=1,
+% 10Hz=2, 8.57Hz=3, 7.5Hz=4, 6.66Hz=5)
+% If the order is wrong, then the "Max" classifier will not work properly
+sti_f = [12,10,8.57,7.5,6.66];
+
+% CCA feat extraction method
+extr = eegtoolkit.featextraction.CCA(sti_f,1:4,128,4);
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [64,640]; % Specify the sample range to be used for each Trial
+ss.channels = 6:9; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+%Configure the classifier
+classif = eegtoolkit.classification.MaxChooser;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {ss,df};
+experiment.featextraction = extr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+% experiment.getExperimentInfo
+% experiment.getTime
\ No newline at end of file
diff --git a/doc/exampleITCCA.html b/doc/exampleITCCA.html
new file mode 100644
index 0000000..8433f34
--- /dev/null
+++ b/doc/exampleITCCA.html
@@ -0,0 +1,90 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleITCCA</title>
+  <meta name="keywords" content="exampleITCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleITCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleITCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleITCCA.m">exampleITCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 m_secs = 0.5:0.5:4;
+0002 <span class="keyword">for</span> ii=1:8
+0003     <span class="keyword">for</span> jj = 1:8
+0004         sess = eegtoolkit.util.Session;
+0005         <span class="comment">% sess.loadAll(4);</span>
+0006         <span class="comment">% sess.loadAll(4);</span>
+0007         sess.loadSubject(4,ii);
+0008         ss = eegtoolkit.preprocessing.SampleSelection;
+0009         ss.channels = 1:8;
+0010         ss.sampleRange = [75,74+256*m_secs(jj)];
+0011         <span class="comment">% ss.sampleRange = [1,1140];</span>
+0012         <span class="comment">% 75:1024+74</span>
+0013         h = fdesign.bandpass(<span class="string">'N,F3dB1,F3dB2'</span>,10,6,80,256);
+0014         d1 = design(h,<span class="string">'butter'</span>);
+0015         df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">%</span>
+0016         df.filt = d1;
+0017         
+0018         refer = eegtoolkit.preprocessing.Rereferencing;
+0019         refer.meanSignal = 1;
+0020         
+0021         extr = eegtoolkit.featextraction.RawSignal;
+0022         
+0023         classif = eegtoolkit.classification.ITCCA;
+0024         classif.baseClassifier = eegtoolkit.classification.MaxChooser;
+0025         
+0026         experiment = eegtoolkit.experiment.Experimenter;
+0027         experiment.session = sess;
+0028         experiment.preprocessing = {ss,refer,df};
+0029         experiment.featextraction = extr;
+0030         experiment.classification = classif;
+0031         <span class="comment">% experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;</span>
+0032         <span class="comment">% experiment.run();</span>
+0033         experiment.evalMethod = experiment.EVAL_METHOD_LOBO;
+0034         experiment.run();
+0035         <span class="keyword">for</span> i=1:length(experiment.results)
+0036             accuracy(i) = experiment.results{i}.getAccuracy();
+0037         <span class="keyword">end</span>
+0038         acc2(ii,jj) = mean(accuracy);
+0039         <span class="comment">% accuracy = experiment.results{1}.getAccuracy();</span>
+0040         
+0041     <span class="keyword">end</span>
+0042 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleITCCA.m b/doc/exampleITCCA.m
new file mode 100644
index 0000000..c20387a
--- /dev/null
+++ b/doc/exampleITCCA.m
@@ -0,0 +1,42 @@
+m_secs = 0.5:0.5:4;
+for ii=1:8
+    for jj = 1:8
+        sess = eegtoolkit.util.Session;
+        % sess.loadAll(4);
+        % sess.loadAll(4);
+        sess.loadSubject(4,ii);
+        ss = eegtoolkit.preprocessing.SampleSelection;
+        ss.channels = 1:8;
+        ss.sampleRange = [75,74+256*m_secs(jj)];
+        % ss.sampleRange = [1,1140];
+        % 75:1024+74
+        h = fdesign.bandpass('N,F3dB1,F3dB2',10,6,80,256);
+        d1 = design(h,'butter');
+        df = eegtoolkit.preprocessing.DigitalFilter; %
+        df.filt = d1;
+        
+        refer = eegtoolkit.preprocessing.Rereferencing;
+        refer.meanSignal = 1;
+        
+        extr = eegtoolkit.featextraction.RawSignal;
+        
+        classif = eegtoolkit.classification.ITCCA;
+        classif.baseClassifier = eegtoolkit.classification.MaxChooser;
+        
+        experiment = eegtoolkit.experiment.Experimenter;
+        experiment.session = sess;
+        experiment.preprocessing = {ss,refer,df};
+        experiment.featextraction = extr;
+        experiment.classification = classif;
+        % experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+        % experiment.run();
+        experiment.evalMethod = experiment.EVAL_METHOD_LOBO;
+        experiment.run();
+        for i=1:length(experiment.results)
+            accuracy(i) = experiment.results{i}.getAccuracy();
+        end
+        acc2(ii,jj) = mean(accuracy);
+        % accuracy = experiment.results{1}.getAccuracy();
+        
+    end
+end
\ No newline at end of file
diff --git a/doc/exampleL1MCCA.html b/doc/exampleL1MCCA.html
new file mode 100644
index 0000000..511922c
--- /dev/null
+++ b/doc/exampleL1MCCA.html
@@ -0,0 +1,89 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleL1MCCA</title>
+  <meta name="keywords" content="exampleL1MCCA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleL1MCCA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleL1MCCA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleL1MCCA.m">exampleL1MCCA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 
+0002 sess = eegtoolkit.util.Session;
+0003 sess.loadSubject(4,1);
+0004 <span class="comment">% load filters/epocfilter;</span>
+0005 
+0006 sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];<span class="comment">%Reference signals -</span>
+0007 extr = eegtoolkit.featextraction.L1MCCA;
+0008 
+0009 refer = eegtoolkit.preprocessing.Rereferencing;
+0010 refer.meanSignal = 1;
+0011 
+0012 [z,p,k]=butter(3,[6,80]/128);
+0013 <span class="comment">% [z,p,k]=butter(3,[5,48]/125);</span>
+0014 [s,g]=zp2sos(z,p,k);
+0015 Hd = dfilt.df2sos(s,g);
+0016 
+0017 m_secs = 5;
+0018 ss = eegtoolkit.preprocessing.SampleSelection;
+0019 ss.sampleRange = [1,1114]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0020 ss.channels = [1:8];<span class="comment">%Specify the channel(s) to be used</span>
+0021 <span class="comment">%</span>
+0022 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0023 df.filt = Hd; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0024 
+0025 lcca = eegtoolkit.classification.L1MCCA(256,1114/256,4,sti_f);
+0026 
+0027 experiment = eegtoolkit.experiment.Experimenter;
+0028 experiment.session = sess;
+0029 experiment.preprocessing = {ss,refer,df};<span class="comment">% Order of preprocessing steps matters.</span>
+0030 experiment.featextraction = extr;
+0031 experiment.classification = lcca;
+0032 experiment.evalMethod = experiment.EVAL_METHOD_LOBO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0033 <span class="comment">%run the experiment</span>
+0034 experiment.run();
+0035 accuracies = [];
+0036 <span class="keyword">for</span> i=1:length(experiment.results)
+0037     accuracies(i) = experiment.results{i}.getAccuracy();    
+0038 <span class="keyword">end</span>
+0039 accuracies'
+0040 <span class="comment">%mean accuracy for all subjects</span>
+0041 fprintf(<span class="string">'mean acc = %.2f\n'</span>, mean(accuracies));</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleL1MCCA.m b/doc/exampleL1MCCA.m
new file mode 100644
index 0000000..ed3ead9
--- /dev/null
+++ b/doc/exampleL1MCCA.m
@@ -0,0 +1,41 @@
+
+sess = eegtoolkit.util.Session;
+sess.loadSubject(4,1);
+% load filters/epocfilter;
+
+sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];%Reference signals -
+extr = eegtoolkit.featextraction.L1MCCA;
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+refer.meanSignal = 1;
+
+[z,p,k]=butter(3,[6,80]/128);
+% [z,p,k]=butter(3,[5,48]/125);
+[s,g]=zp2sos(z,p,k);
+Hd = dfilt.df2sos(s,g);
+
+m_secs = 5;
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [1,1114]; % Specify the sample range to be used for each Trial
+ss.channels = [1:8];%Specify the channel(s) to be used
+% 
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hd; % Hbp is a filter built with "filterbuilder" matlab function
+
+lcca = eegtoolkit.classification.L1MCCA(256,1114/256,4,sti_f);
+
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {ss,refer,df};% Order of preprocessing steps matters.
+experiment.featextraction = extr;
+experiment.classification = lcca;
+experiment.evalMethod = experiment.EVAL_METHOD_LOBO; % specify that you want a "leave one subject out" (default is LOOCV)
+%run the experiment
+experiment.run();
+accuracies = [];
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();    
+end
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %.2f\n', mean(accuracies));
\ No newline at end of file
diff --git a/doc/exampleLSL.html b/doc/exampleLSL.html
new file mode 100644
index 0000000..d086b38
--- /dev/null
+++ b/doc/exampleLSL.html
@@ -0,0 +1,109 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleLSL</title>
+  <meta name="keywords" content="exampleLSL">
+  <meta name="description" content="Add dependencies to the Matlab path, LibLSL is required for this example">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleLSL.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleLSL
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Add dependencies to the Matlab path, LibLSL is required for this example</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment">Add dependencies to the Matlab path, LibLSL is required for this example
+to work</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleLSL.m">exampleLSL.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">%Add dependencies to the Matlab path, LibLSL is required for this example</span>
+0002 <span class="comment">%to work</span>
+0003 addpath liblsl-Matlab\;
+0004 addpath liblsl-Matlab\bin\;
+0005 addpath liblsl-Matlab\mex\;
+0006 <span class="comment">%Initialize LSL Wrapper class</span>
+0007 lsl = eegtoolkit.util.LSLWrapper;
+0008 <span class="comment">%Declare the name of the stream that will contain the EEG data</span>
+0009 datastream = <span class="string">'EMOTIVStream'</span>;
+0010 <span class="comment">%Declare the name of the stream through which the events will be</span>
+0011 <span class="comment">%communicated</span>
+0012 eventstream = <span class="string">'MyEventStream'</span>;
+0013 <span class="comment">%Size of signal that will be used for the recognition task</span>
+0014 bufferSize = 5; <span class="comment">%in seconds</span>
+0015 <span class="comment">%The event code that will trigger the recognition task</span>
+0016 eventCode = 100;
+0017  
+0018  
+0019 <span class="comment">% RECOGNITION ALGORITHM CONFIGURATION</span>
+0020  
+0021 <span class="comment">%Indicate the number of stimuli (5) and their frequencies</span>
+0022 stimulus_frequencies = [12 10 8.57 7.5 6.66];
+0023  
+0024 <span class="comment">%Filtering the eeg data</span>
+0025 <span class="comment">% df = eegtoolkit.preprocessing.DigitalFilter;</span>
+0026 <span class="comment">% %This filter was created via the 'filterbuilder' method of Matlab</span>
+0027 <span class="comment">% df.filt = Hbp;</span>
+0028  
+0029 <span class="comment">%Indicate which channels of the data (different electrodes) will be used</span>
+0030 ss = eegtoolkit.preprocessing.SampleSelection;
+0031 <span class="comment">%We will use all EPOC channels for this example</span>
+0032 channels = 1:1:14;
+0033 ss.channels = channels;
+0034 ss.sampleRange = [1,128];
+0035  
+0036 <span class="comment">%Sampling rate for the EPOC headset is 128Hz</span>
+0037 samplingRate = 128;
+0038  
+0039 <span class="comment">%Another required parameter for the CCA algorithm</span>
+0040 numberOfHarmonics = 4;
+0041 <span class="comment">%Initialize the Canonical Correlation Analysis class for the stimuli</span>
+0042 <span class="comment">%recognition</span>
+0043 cca = eegtoolkit.featextraction.CCA(stimulus_frequencies,channels,samplingRate,numberOfHarmonics);
+0044  
+0045 <span class="comment">%Simple classifier that uses the max value of the features to assign the</span>
+0046 <span class="comment">%label</span>
+0047 maxC = eegtoolkit.classification.MaxChooser;
+0048  
+0049 <span class="comment">%Assign the algorithm configuration to the LSL Wrapper class</span>
+0050 lsl.preprocessing = {ss};
+0051 lsl.featextraction = cca;
+0052 lsl.classification = maxC;
+0053  
+0054 <span class="comment">%Find the streams in the network</span>
+0055 lsl.resolveStreams(datastream,bufferSize,eventstream);
+0056 <span class="comment">%Pause for 5 seconds to allow the stream to gather some data</span>
+0057 pause(bufferSize); 
+0058 <span class="comment">%Run the recognition task. The task runs indefinetely until is specifically</span>
+0059 <span class="comment">%interrupted</span>
+0060 lsl.runSSVEP(eventCode);</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleLSL.m b/doc/exampleLSL.m
new file mode 100644
index 0000000..51b2e2a
--- /dev/null
+++ b/doc/exampleLSL.m
@@ -0,0 +1,60 @@
+%Add dependencies to the Matlab path, LibLSL is required for this example
+%to work
+addpath liblsl-Matlab\;
+addpath liblsl-Matlab\bin\;
+addpath liblsl-Matlab\mex\;
+%Initialize LSL Wrapper class
+lsl = eegtoolkit.util.LSLWrapper;
+%Declare the name of the stream that will contain the EEG data
+datastream = 'EMOTIVStream';
+%Declare the name of the stream through which the events will be
+%communicated
+eventstream = 'MyEventStream';
+%Size of signal that will be used for the recognition task
+bufferSize = 5; %in seconds
+%The event code that will trigger the recognition task
+eventCode = 100;
+ 
+ 
+% RECOGNITION ALGORITHM CONFIGURATION
+ 
+%Indicate the number of stimuli (5) and their frequencies
+stimulus_frequencies = [12 10 8.57 7.5 6.66];
+ 
+%Filtering the eeg data
+% df = eegtoolkit.preprocessing.DigitalFilter;
+% %This filter was created via the 'filterbuilder' method of Matlab
+% df.filt = Hbp; 
+ 
+%Indicate which channels of the data (different electrodes) will be used
+ss = eegtoolkit.preprocessing.SampleSelection;
+%We will use all EPOC channels for this example
+channels = 1:1:14;
+ss.channels = channels;
+ss.sampleRange = [1,128];
+ 
+%Sampling rate for the EPOC headset is 128Hz
+samplingRate = 128;
+ 
+%Another required parameter for the CCA algorithm
+numberOfHarmonics = 4;
+%Initialize the Canonical Correlation Analysis class for the stimuli
+%recognition
+cca = eegtoolkit.featextraction.CCA(stimulus_frequencies,channels,samplingRate,numberOfHarmonics);
+ 
+%Simple classifier that uses the max value of the features to assign the
+%label
+maxC = eegtoolkit.classification.MaxChooser;
+ 
+%Assign the algorithm configuration to the LSL Wrapper class
+lsl.preprocessing = {ss};
+lsl.featextraction = cca;
+lsl.classification = maxC;
+ 
+%Find the streams in the network
+lsl.resolveStreams(datastream,bufferSize,eventstream);
+%Pause for 5 seconds to allow the stream to gather some data
+pause(bufferSize); 
+%Run the recognition task. The task runs indefinetely until is specifically
+%interrupted
+lsl.runSSVEP(eventCode);
diff --git a/doc/exampleLateFusion.html b/doc/exampleLateFusion.html
new file mode 100644
index 0000000..19913ed
--- /dev/null
+++ b/doc/exampleLateFusion.html
@@ -0,0 +1,126 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleLateFusion</title>
+  <meta name="keywords" content="exampleLateFusion">
+  <meta name="description" content="Leave one subject out testing">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleLateFusion.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleLateFusion
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Leave one subject out testing</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Leave one subject out testing
+ load filtMAMEM; % load a filter
+ sess = eegtoolkit.util.Session(Hhp);
+ sess.loadAll(1); %its best to do this once, outside the script (too much
+ time)
+ transf = eegtoolkit.transformer.PWelchTransformer();
+ Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(1); %Loads dataset I</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleLateFusion.m">exampleLateFusion.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Leave one subject out testing</span>
+0002 <span class="comment">% load filtMAMEM; % load a filter</span>
+0003 <span class="comment">% sess = eegtoolkit.util.Session(Hhp);</span>
+0004 <span class="comment">% sess.loadAll(1); %its best to do this once, outside the script (too much</span>
+0005 <span class="comment">% time)</span>
+0006 <span class="comment">% transf = eegtoolkit.transformer.PWelchTransformer();</span>
+0007 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0008 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0009 <span class="comment">% Matlab path</span>
+0010 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0011 <span class="comment">% sess.loadAll(1); %Loads dataset I</span>
+0012 
+0013 <span class="comment">%Load a filter from the samples</span>
+0014 load filters/filt_IIRElliptic;
+0015 
+0016 
+0017 
+0018 refer = eegtoolkit.preprocessing.Rereferencing;
+0019 <span class="comment">%Subtract the mean from the signal</span>
+0020 refer.meanSignal = 1;
+0021 
+0022 ss = eegtoolkit.preprocessing.SampleSelection;
+0023 ss.sampleRange = [1,1250]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0024 ss.channels = [138,139,150]; <span class="comment">% Specify the channel(s) to be used</span>
+0025 
+0026 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0027 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0028 
+0029 
+0030 <span class="comment">%Extract features with the pwelch method</span>
+0031 extr1 = eegtoolkit.featextraction.PWelch;
+0032 extr1.channel = 1; <span class="comment">% will use channel 138</span>
+0033 
+0034 extr2 = eegtoolkit.featextraction.PWelch;
+0035 extr2.channel = 2; <span class="comment">% will use channel 139</span>
+0036 
+0037 extr3 = eegtoolkit.featextraction.PWelch;
+0038 extr3.channel = 3; <span class="comment">% will use channel 150</span>
+0039 
+0040 extr = {extr1,extr2,extr3};
+0041 <span class="comment">% Generate a special feature vector to be used with fusion classifier</span>
+0042 aggr = eegtoolkit.aggregation.LateFusion;
+0043 <span class="comment">%Configure the classifier</span>
+0044 <span class="comment">% Generate 3 instances of the &quot;baseClassifier&quot; and output the label by</span>
+0045 <span class="comment">% majority vote</span>
+0046 classif = eegtoolkit.classification.FusionClassifierWrapper;
+0047 classif.baseClassifier = eegtoolkit.classification.LIBSVM;
+0048 
+0049 <span class="comment">%Set the Experimenter wrapper class</span>
+0050 experiment = eegtoolkit.experiment.Experimenter;
+0051 experiment.session = sess;
+0052 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0053 experiment.preprocessing = {ss,refer,df};
+0054 experiment.featextraction = {extr1,extr2,extr3};
+0055 experiment.aggregator = aggr;
+0056 experiment.classification = classif;
+0057 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0058 experiment.run();
+0059 <span class="keyword">for</span> i=1:length(experiment.results)
+0060     accuracies(i) = experiment.results{i}.getAccuracy();
+0061 <span class="keyword">end</span>
+0062 
+0063 accuracies'
+0064 <span class="comment">%mean accuracy for all subjects</span>
+0065 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0066 <span class="comment">%get the configuration used (for reporting)</span>
+0067 experiment.getExperimentInfo
+0068 experiment.getTime</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleLateFusion.m b/doc/exampleLateFusion.m
new file mode 100644
index 0000000..259bf3e
--- /dev/null
+++ b/doc/exampleLateFusion.m
@@ -0,0 +1,68 @@
+% Leave one subject out testing
+% load filtMAMEM; % load a filter
+% sess = eegtoolkit.util.Session(Hhp);
+% sess.loadAll(1); %its best to do this once, outside the script (too much
+% time)
+% transf = eegtoolkit.transformer.PWelchTransformer();
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(1); %Loads dataset I
+
+%Load a filter from the samples
+load filters/filt_IIRElliptic;
+
+
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [1,1250]; % Specify the sample range to be used for each Trial
+ss.channels = [138,139,150]; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+
+%Extract features with the pwelch method
+extr1 = eegtoolkit.featextraction.PWelch;
+extr1.channel = 1; % will use channel 138
+
+extr2 = eegtoolkit.featextraction.PWelch;
+extr2.channel = 2; % will use channel 139
+
+extr3 = eegtoolkit.featextraction.PWelch;
+extr3.channel = 3; % will use channel 150
+
+extr = {extr1,extr2,extr3};
+% Generate a special feature vector to be used with fusion classifier
+aggr = eegtoolkit.aggregation.LateFusion;
+%Configure the classifier
+% Generate 3 instances of the "baseClassifier" and output the label by
+% majority vote
+classif = eegtoolkit.classification.FusionClassifierWrapper;
+classif.baseClassifier = eegtoolkit.classification.LIBSVM;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {ss,refer,df};
+experiment.featextraction = {extr1,extr2,extr3};
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+experiment.getExperimentInfo
+experiment.getTime
\ No newline at end of file
diff --git a/doc/exampleMotorPWelch.html b/doc/exampleMotorPWelch.html
new file mode 100644
index 0000000..a690fd6
--- /dev/null
+++ b/doc/exampleMotorPWelch.html
@@ -0,0 +1,83 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleMotorPWelch</title>
+  <meta name="keywords" content="exampleMotorPWelch">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleMotorPWelch.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleMotorPWelch
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleMotorPWelch.m">exampleMotorPWelch.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 sess = eegtoolkit.util.Session;
+0002 sess.loadAll(6);
+0003 <span class="comment">%</span>
+0004 
+0005 <span class="comment">% load('testingMotorVag1');</span>
+0006 <span class="comment">% % load</span>
+0007 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0008 <span class="comment">% % sess.loadMOTOR(labels,trials);</span>
+0009 <span class="comment">% sess.loadVag(trials,labels);</span>
+0010 
+0011 ss = eegtoolkit.preprocessing.SampleSelection;
+0012 ss.channels = [1,3];
+0013 ss.sampleRange = [384,896];
+0014 
+0015 extr1  = eegtoolkit.featextraction.PWelch;
+0016 extr1.channel = 1;
+0017 
+0018 extr2 = eegtoolkit.featextraction.PWelch;
+0019 extr2.channel = 2;
+0020 
+0021 aggr = eegtoolkit.aggregation.ChannelConcat;
+0022 
+0023 classif = eegtoolkit.classification.MLR;
+0024 experiment = eegtoolkit.experiment.Experimenter;
+0025 experiment.session = sess;
+0026 experiment.preprocessing = {ss};
+0027 experiment.featextraction = {extr1, extr2};
+0028 experiment.aggregator = aggr;
+0029 experiment.classification = classif;
+0030 experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+0031 <span class="comment">% experiment.run();</span>
+0032 <span class="comment">% experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;</span>
+0033 experiment.run();
+0034 accuracy = experiment.results{1}.getAccuracy();
+0035</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleMotorPWelch.m b/doc/exampleMotorPWelch.m
new file mode 100644
index 0000000..76f83cc
--- /dev/null
+++ b/doc/exampleMotorPWelch.m
@@ -0,0 +1,35 @@
+sess = eegtoolkit.util.Session;
+sess.loadAll(6);
+% 
+
+% load('testingMotorVag1');
+% % load
+% sess = eegtoolkit.util.Session;
+% % sess.loadMOTOR(labels,trials);
+% sess.loadVag(trials,labels);
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.channels = [1,3];
+ss.sampleRange = [384,896];
+
+extr1  = eegtoolkit.featextraction.PWelch;
+extr1.channel = 1;
+
+extr2 = eegtoolkit.featextraction.PWelch;
+extr2.channel = 2;
+
+aggr = eegtoolkit.aggregation.ChannelConcat;
+
+classif = eegtoolkit.classification.MLR;
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {ss};
+experiment.featextraction = {extr1, extr2};
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+% experiment.run();
+% experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+experiment.run();
+accuracy = experiment.results{1}.getAccuracy();
+
diff --git a/doc/exampleOptimal.html b/doc/exampleOptimal.html
new file mode 100644
index 0000000..5d10b31
--- /dev/null
+++ b/doc/exampleOptimal.html
@@ -0,0 +1,107 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleOptimal</title>
+  <meta name="keywords" content="exampleOptimal">
+  <meta name="description" content="Load the data. Call this once outside of the script so you dont have to">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleOptimal.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleOptimal
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>Load the data. Call this once outside of the script so you dont have to</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> Load the data. Call this once outside of the script so you dont have to
+ load the data again and again. Make sure the dataset is included in your
+ Matlab path
+ sess = eegtoolkit.util.Session;
+ sess.loadAll(1); %Loads dataset I</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleOptimal.m">exampleOptimal.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% Load the data. Call this once outside of the script so you dont have to</span>
+0002 <span class="comment">% load the data again and again. Make sure the dataset is included in your</span>
+0003 <span class="comment">% Matlab path</span>
+0004 <span class="comment">% sess = eegtoolkit.util.Session;</span>
+0005 <span class="comment">% sess.loadAll(1); %Loads dataset I</span>
+0006 
+0007 <span class="comment">%Load a filter from the samples</span>
+0008 load filters/filt_IIRElliptic;
+0009 
+0010 extr = eegtoolkit.featextraction.PWelchExperimental;
+0011 extr.nfft = 512;
+0012 extr.over_len = 0.75;
+0013 extr.win_len = 350;
+0014 
+0015 amu = eegtoolkit.preprocessing.Amuse;
+0016 amu.first = 15;
+0017 amu.last = 252;
+0018 
+0019 refer = eegtoolkit.preprocessing.Rereferencing;
+0020 <span class="comment">%Subtract the mean from the signal</span>
+0021 refer.meanSignal = 1;
+0022 
+0023 ss = eegtoolkit.preprocessing.SampleSelection;
+0024 ss.sampleRange = [1,1250]; <span class="comment">% Specify the sample range to be used for each Trial</span>
+0025 ss.channels = 138; <span class="comment">% Specify the channel(s) to be used</span>
+0026 
+0027 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0028 df.filt = Hbp; <span class="comment">% Hbp is a filter built with &quot;filterbuilder&quot; matlab function</span>
+0029 
+0030 svd = eegtoolkit.featselection.SVD;
+0031 svd.modes = 90;
+0032 
+0033 <span class="comment">%Configure the classifier</span>
+0034 classif = eegtoolkit.classification.LIBSVMFast;
+0035 
+0036 <span class="comment">%Set the Experimenter wrapper class</span>
+0037 experiment = eegtoolkit.experiment.Experimenter;
+0038 experiment.session = sess;
+0039 <span class="comment">% Add the preprocessing steps (order is taken into account)</span>
+0040 experiment.preprocessing = {amu,ss,refer,df};
+0041 experiment.featselection = svd;
+0042 experiment.featextraction = extr;
+0043 experiment.classification = classif;
+0044 experiment.evalMethod = experiment.EVAL_METHOD_LOSO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0045 experiment.run();
+0046 <span class="keyword">for</span> i=1:length(experiment.results)
+0047     accuracies(i) = experiment.results{i}.getAccuracy();
+0048 <span class="keyword">end</span>
+0049 
+0050 accuracies'
+0051 <span class="comment">%mean accuracy for all subjects</span>
+0052 fprintf(<span class="string">'mean acc = %f\n'</span>, mean(accuracies));
+0053 <span class="comment">%get the configuration used (for reporting)</span>
+0054 experiment.getExperimentInfo
+0055 experiment.getTime</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleOptimal.m b/doc/exampleOptimal.m
new file mode 100644
index 0000000..36573f7
--- /dev/null
+++ b/doc/exampleOptimal.m
@@ -0,0 +1,55 @@
+% Load the data. Call this once outside of the script so you dont have to
+% load the data again and again. Make sure the dataset is included in your
+% Matlab path
+% sess = eegtoolkit.util.Session;
+% sess.loadAll(1); %Loads dataset I
+
+%Load a filter from the samples
+load filters/filt_IIRElliptic;
+
+extr = eegtoolkit.featextraction.PWelchExperimental;
+extr.nfft = 512;
+extr.over_len = 0.75;
+extr.win_len = 350;
+
+amu = eegtoolkit.preprocessing.Amuse;
+amu.first = 15;
+amu.last = 252;
+
+refer = eegtoolkit.preprocessing.Rereferencing;
+%Subtract the mean from the signal
+refer.meanSignal = 1;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.sampleRange = [1,1250]; % Specify the sample range to be used for each Trial
+ss.channels = 138; % Specify the channel(s) to be used
+
+df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+df.filt = Hbp; % Hbp is a filter built with "filterbuilder" matlab function
+
+svd = eegtoolkit.featselection.SVD;
+svd.modes = 90;
+
+%Configure the classifier
+classif = eegtoolkit.classification.LIBSVMFast;
+
+%Set the Experimenter wrapper class
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+% Add the preprocessing steps (order is taken into account)
+experiment.preprocessing = {amu,ss,refer,df};
+experiment.featselection = svd;
+experiment.featextraction = extr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_LOSO; % specify that you want a "leave one subject out" (default is LOOCV)
+experiment.run();
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+%mean accuracy for all subjects
+fprintf('mean acc = %f\n', mean(accuracies));
+%get the configuration used (for reporting)
+experiment.getExperimentInfo
+experiment.getTime
diff --git a/doc/exampleSMFA.html b/doc/exampleSMFA.html
new file mode 100644
index 0000000..8e07a8b
--- /dev/null
+++ b/doc/exampleSMFA.html
@@ -0,0 +1,163 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleSMFA</title>
+  <meta name="keywords" content="exampleSMFA">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleSMFA.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleSMFA
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleSMFA.m">exampleSMFA.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 clear
+0002 
+0003 <span class="comment">% fileID = fopen('SMFA_Results.txt','a');</span>
+0004 <span class="keyword">for</span> subn=1:10
+0005     
+0006     <span class="comment">%Dataset 4</span>
+0007     sess = eegtoolkit.util.Session;
+0008     <span class="comment">% sess.loadAll(4);</span>
+0009     sess.loadSubject(4,subn);
+0010     
+0011     <span class="comment">% %Dataset 2</span>
+0012     <span class="comment">% sess = ssveptoolkit.util.Session;</span>
+0013     <span class="comment">% sess.loadAll(2);</span>
+0014     
+0015     load filters/filt_IIRElliptic;
+0016     
+0017     <span class="comment">%Dataset 4</span>
+0018     <span class="comment">% sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];</span>
+0019     <span class="comment">% extr = ssveptoolkit.featextraction.CCA(sti_f,[1:8],256,4);</span>
+0020     
+0021     extr = eegtoolkit.featextraction.MLR_Transf(1:8);
+0022     <span class="comment">%         sti_f = [9.25, 9.75, 10.25, 10.75, 11.25, 11.75, 12.25, 12.75, 13.25, 13.75, 14.25, 14.75];</span>
+0023     <span class="comment">%         extr = ssveptoolkit.featextraction.CCA(sti_f,1:8,256,4);</span>
+0024     
+0025     <span class="comment">%%Dataset 2</span>
+0026     <span class="comment">% sti_f = [12 10 8.57 7.50 6.66];</span>
+0027     <span class="comment">% sti_f = [6.66 7.5 8.57 10 12];</span>
+0028     <span class="comment">% extr = ssveptoolkit.featextraction.CCA(sti_f,[1:2],250,4);</span>
+0029     
+0030     <span class="comment">% extr = ssveptoolkit.featextraction.OMP(sti_f,[1:2],250,4,16,0);</span>
+0031     <span class="comment">%sti_f: reference signals</span>
+0032     <span class="comment">%[1:2]: input=2 channels. Depends on what you set on &quot;ss.channels&quot; e.g. if</span>
+0033     <span class="comment">%you select 10 channels you need to set &quot;[1:10]&quot;</span>
+0034     <span class="comment">%250: sampling rate (Dataset 1&amp;2=250)</span>
+0035     <span class="comment">%4: number of harmonics of the reference signals</span>
+0036     
+0037     <span class="comment">% %Dataset 2</span>
+0038     <span class="comment">% amu = ssveptoolkit.preprocessing.Amuse;</span>
+0039     <span class="comment">% amu.first = 15;</span>
+0040     <span class="comment">% amu.last = 252;</span>
+0041     
+0042     refer = eegtoolkit.preprocessing.Rereferencing;
+0043     <span class="comment">%Subtract the mean from the signal</span>
+0044     refer.meanSignal = 1;
+0045     
+0046     <span class="comment">%Dataset 4</span>
+0047     <span class="comment">% m_secs = 2;</span>
+0048     
+0049     <span class="comment">% %Dataset 2</span>
+0050     <span class="comment">% m_secs = 5;</span>
+0051     
+0052     ss = eegtoolkit.preprocessing.SampleSelection;
+0053     
+0054     <span class="comment">%Dataset 4</span>
+0055     onset=39;
+0056     <span class="comment">%delay of the visual system</span>
+0057     visual_delay = 35;
+0058     ss.sampleRange = [onset+visual_delay+1,onset+visual_delay+1*256];
+0059     ss.channels = 1:8;
+0060     <span class="comment">% ss.channels = 7;</span>
+0061     
+0062     <span class="comment">% %Dataset 2</span>
+0063     <span class="comment">% ss.sampleRange = [1,250*m_secs]; % Specify the sample range to be used for each Trial</span>
+0064     <span class="comment">% % ss.channels = [116,126,137,138,139,147,150];%[126,138]%Specify the channel(s) to be used</span>
+0065     <span class="comment">% ss.channels = [126,138];</span>
+0066     
+0067     <span class="comment">%Dataset 4</span>
+0068     df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">% Apply a filter to the raw data</span>
+0069     [z,p,k]=butter(3,[6,80]/128);
+0070     [s,g]=zp2sos(z,p,k);
+0071     Hd = dfilt.df2sos(s,g);
+0072     df.filt = Hd;
+0073     
+0074     Res = zeros(length(1:4:10),length(1:4:100));
+0075     
+0076     <span class="comment">% Set parameter grid to search</span>
+0077     <span class="comment">%         for qq=1:10</span>
+0078     <span class="comment">%             for ww=1:25</span>
+0079     
+0080     <span class="comment">%Number of subclasses per class</span>
+0081     NumS = 2*ones(1,12);
+0082     
+0083     S = 0.4;
+0084     <span class="comment">%                 kInt = qq;</span>
+0085     <span class="comment">%                 kPen = 4*(ww-1)+1;</span>
+0086     kInt = 3;
+0087     kPen = 50;
+0088     classif = eegtoolkit.classification.SMFA(0,NumS,S,kInt,kPen);
+0089     
+0090     experiment = eegtoolkit.experiment.Experimenter;
+0091     experiment.session = sess;
+0092     
+0093     <span class="comment">%Dataset 4</span>
+0094     experiment.preprocessing = {ss,refer,df};
+0095     
+0096     <span class="comment">% %Dataset 2</span>
+0097     <span class="comment">% experiment.preprocessing = {amu,ss,refer,df};% Order of preprocessing steps matters.</span>
+0098     
+0099     experiment.featextraction = extr;
+0100     experiment.classification = classif;
+0101     experiment.evalMethod = experiment.EVAL_METHOD_LOBO; <span class="comment">% specify that you want a &quot;leave one subject out&quot; (default is LOOCV)</span>
+0102     <span class="comment">% experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;</span>
+0103     
+0104     <span class="comment">%run the experiment</span>
+0105     experiment.run();
+0106     accuracies = [];
+0107     <span class="keyword">for</span> i=1:length(experiment.results)
+0108         accuracies(i) = experiment.results{i}.getAccuracy();
+0109     <span class="keyword">end</span>
+0110     <span class="comment">% accuracies'</span>
+0111     <span class="comment">% mean accuracy for all subjects</span>
+0112 <span class="comment">%     fprintf('mean acc = %.2f\n', mean(accuracies));</span>
+0113     subaccuracies(subn) = mean(accuracies);
+0114 <span class="keyword">end</span>
+0115 fprintf(<span class="string">'mean acc for all subjects %.2f\n'</span>,mean(subaccuracies));</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleSMFA.m b/doc/exampleSMFA.m
new file mode 100644
index 0000000..15a580d
--- /dev/null
+++ b/doc/exampleSMFA.m
@@ -0,0 +1,115 @@
+clear
+
+% fileID = fopen('SMFA_Results.txt','a');
+for subn=1:10
+    
+    %Dataset 4
+    sess = eegtoolkit.util.Session;
+    % sess.loadAll(4);
+    sess.loadSubject(4,subn);
+    
+    % %Dataset 2
+    % sess = ssveptoolkit.util.Session;
+    % sess.loadAll(2);
+    
+    load filters/filt_IIRElliptic;
+    
+    %Dataset 4
+    % sti_f = [9.25, 11.25, 13.25, 9.75, 11.75, 13.75, 10.25, 12.25, 14.25, 10.75, 12.75, 14.75];
+    % extr = ssveptoolkit.featextraction.CCA(sti_f,[1:8],256,4);
+    
+    extr = eegtoolkit.featextraction.MLR_Transf(1:8);
+    %         sti_f = [9.25, 9.75, 10.25, 10.75, 11.25, 11.75, 12.25, 12.75, 13.25, 13.75, 14.25, 14.75];
+    %         extr = ssveptoolkit.featextraction.CCA(sti_f,1:8,256,4);
+    
+    %%Dataset 2
+    % sti_f = [12 10 8.57 7.50 6.66];
+    % sti_f = [6.66 7.5 8.57 10 12];
+    % extr = ssveptoolkit.featextraction.CCA(sti_f,[1:2],250,4);
+    
+    % extr = ssveptoolkit.featextraction.OMP(sti_f,[1:2],250,4,16,0);
+    %sti_f: reference signals
+    %[1:2]: input=2 channels. Depends on what you set on "ss.channels" e.g. if
+    %you select 10 channels you need to set "[1:10]"
+    %250: sampling rate (Dataset 1&2=250)
+    %4: number of harmonics of the reference signals
+    
+    % %Dataset 2
+    % amu = ssveptoolkit.preprocessing.Amuse;
+    % amu.first = 15;
+    % amu.last = 252;
+    
+    refer = eegtoolkit.preprocessing.Rereferencing;
+    %Subtract the mean from the signal
+    refer.meanSignal = 1;
+    
+    %Dataset 4
+    % m_secs = 2;
+    
+    % %Dataset 2
+    % m_secs = 5;
+    
+    ss = eegtoolkit.preprocessing.SampleSelection;
+    
+    %Dataset 4
+    onset=39;
+    %delay of the visual system
+    visual_delay = 35;
+    ss.sampleRange = [onset+visual_delay+1,onset+visual_delay+1*256];
+    ss.channels = 1:8;
+    % ss.channels = 7;
+    
+    % %Dataset 2
+    % ss.sampleRange = [1,250*m_secs]; % Specify the sample range to be used for each Trial
+    % % ss.channels = [116,126,137,138,139,147,150];%[126,138]%Specify the channel(s) to be used
+    % ss.channels = [126,138];
+    
+    %Dataset 4
+    df = eegtoolkit.preprocessing.DigitalFilter; % Apply a filter to the raw data
+    [z,p,k]=butter(3,[6,80]/128);
+    [s,g]=zp2sos(z,p,k);
+    Hd = dfilt.df2sos(s,g);
+    df.filt = Hd;
+    
+    Res = zeros(length(1:4:10),length(1:4:100));
+    
+    % Set parameter grid to search
+    %         for qq=1:10
+    %             for ww=1:25
+    
+    %Number of subclasses per class
+    NumS = 2*ones(1,12);
+    
+    S = 0.4;
+    %                 kInt = qq;
+    %                 kPen = 4*(ww-1)+1;
+    kInt = 3;
+    kPen = 50;
+    classif = eegtoolkit.classification.SMFA(0,NumS,S,kInt,kPen);
+    
+    experiment = eegtoolkit.experiment.Experimenter;
+    experiment.session = sess;
+    
+    %Dataset 4
+    experiment.preprocessing = {ss,refer,df};
+    
+    % %Dataset 2
+    % experiment.preprocessing = {amu,ss,refer,df};% Order of preprocessing steps matters.
+    
+    experiment.featextraction = extr;
+    experiment.classification = classif;
+    experiment.evalMethod = experiment.EVAL_METHOD_LOBO; % specify that you want a "leave one subject out" (default is LOOCV)
+    % experiment.evalMethod = experiment.EVAL_METHOD_LOOCV;
+    
+    %run the experiment
+    experiment.run();
+    accuracies = [];
+    for i=1:length(experiment.results)
+        accuracies(i) = experiment.results{i}.getAccuracy();
+    end
+    % accuracies'
+    % mean accuracy for all subjects
+%     fprintf('mean acc = %.2f\n', mean(accuracies));
+    subaccuracies(subn) = mean(accuracies);
+end
+fprintf('mean acc for all subjects %.2f\n',mean(subaccuracies));
\ No newline at end of file
diff --git a/doc/fortran.png b/doc/fortran.png
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diff --git a/doc/graph.dot b/doc/graph.dot
new file mode 100644
index 0000000..c7af74f
--- /dev/null
+++ b/doc/graph.dot
@@ -0,0 +1,18 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+
+  exampleCSP [URL="exampleCSP.html"];
+  exampleCombiCCA [URL="exampleCombiCCA.html"];
+  exampleDefault [URL="exampleDefault.html"];
+  exampleEPOCCCASVM [URL="exampleEPOCCCASVM.html"];
+  exampleERRP [URL="exampleERRP.html"];
+  exampleEarlyFusion [URL="exampleEarlyFusion.html"];
+  exampleEpoc [URL="exampleEpoc.html"];
+  exampleITCCA [URL="exampleITCCA.html"];
+  exampleL1MCCA [URL="exampleL1MCCA.html"];
+  exampleLSL [URL="exampleLSL.html"];
+  exampleLateFusion [URL="exampleLateFusion.html"];
+  exampleMotorPWelch [URL="exampleMotorPWelch.html"];
+  exampleOptimal [URL="exampleOptimal.html"];
+  exampleSMFA [URL="exampleSMFA.html"];
+}
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diff --git a/doc/graph.html b/doc/graph.html
new file mode 100644
index 0000000..ba4db20
--- /dev/null
+++ b/doc/graph.html
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+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for .</title>
+  <meta name="keywords" content="dependency, graph, dependence, .">
+  <meta name="description" content="Dependency graph for .">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>
+<h1>Dependency Graph for .</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ." border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="exampleCSP.html" title="exampleCSP" alt="" coords="155,29,152,22,141,15,124,10,103,7,80,5,57,7,36,10,19,15,8,22,5,29,8,37,19,43,36,49,57,52,80,53,103,52,124,49,141,43,152,37">
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+<area shape="poly" id="node7" href="exampleEpoc.html" title="exampleEpoc" alt="" coords="1520,29,1516,22,1505,15,1488,10,1466,7,1441,5,1417,7,1395,10,1378,15,1366,22,1362,29,1366,37,1378,43,1395,49,1417,52,1441,53,1466,52,1488,49,1505,43,1516,37">
+<area shape="poly" id="node8" href="exampleITCCA.html" title="exampleITCCA" alt="" coords="1725,29,1720,22,1708,15,1688,10,1663,7,1635,5,1607,7,1582,10,1562,15,1549,22,1545,29,1549,37,1562,43,1582,49,1607,52,1635,53,1663,52,1688,49,1708,43,1720,37">
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+<area shape="poly" id="node10" href="exampleLSL.html" title="exampleLSL" alt="" coords="2130,29,2126,22,2116,15,2099,10,2078,7,2055,5,2031,7,2010,10,1994,15,1983,22,1979,29,1983,37,1994,43,2010,49,2031,52,2055,53,2078,52,2099,49,2116,43,2126,37">
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+<area shape="poly" id="node12" href="exampleMotorPWelch.html" title="exampleMotorPWelch" alt="" coords="2637,29,2631,22,2614,15,2586,10,2552,7,2515,5,2477,7,2443,10,2416,15,2398,22,2392,29,2398,37,2416,43,2443,49,2477,52,2515,53,2552,52,2586,49,2614,43,2631,37">
+<area shape="poly" id="node13" href="exampleOptimal.html" title="exampleOptimal" alt="" coords="2848,29,2844,22,2830,15,2810,10,2784,7,2755,5,2726,7,2700,10,2679,15,2666,22,2661,29,2666,37,2679,43,2700,49,2726,52,2755,53,2784,52,2810,49,2830,43,2844,37">
+<area shape="poly" id="node14" href="exampleSMFA.html" title="exampleSMFA" alt="" coords="3048,29,3043,22,3031,15,3011,10,2987,7,2960,5,2933,7,2909,10,2889,15,2877,22,2872,29,2877,37,2889,43,2909,49,2933,52,2960,53,2987,52,3011,49,3031,43,3043,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/graph.map b/doc/graph.map
new file mode 100644
index 0000000..c98355c
--- /dev/null
+++ b/doc/graph.map
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+<area shape="poly" id="node2" href="exampleCombiCCA.html" title="exampleCombiCCA" alt="" coords="402,29,396,22,380,15,356,10,325,7,291,5,256,7,225,10,201,15,185,22,180,29,185,37,201,43,225,49,256,52,291,53,325,52,356,49,380,43,396,37">
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diff --git a/doc/index.html b/doc/index.html
new file mode 100644
index 0000000..095abe2
--- /dev/null
+++ b/doc/index.html
@@ -0,0 +1,34 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory .</title>
+  <meta name="keywords" content=".">
+  <meta name="description" content="Index for Directory .">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>
+
+<h1>Index for .</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCSP.html">exampleCSP</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCombiCCA.html">exampleCombiCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleDefault.html">exampleDefault</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEPOCCCASVM.html">exampleEPOCCCASVM</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleERRP.html">exampleERRP</a></td><td>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter'); </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEarlyFusion.html">exampleEarlyFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEpoc.html">exampleEpoc</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleITCCA.html">exampleITCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleL1MCCA.html">exampleL1MCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLSL.html">exampleLSL</a></td><td>Add dependencies to the Matlab path, LibLSL is required for this example </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLateFusion.html">exampleLateFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleMotorPWelch.html">exampleMotorPWelch</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleOptimal.html">exampleOptimal</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleSMFA.html">exampleSMFA</a></td><td> </td></tr></table>
+
+
+<h2>Subsequent directories:</h2>
+<ul style="list-style-image:url(../matlabicon.gif)">
+<li>+eegtoolkit</li><li>.git</li><li>doc</li><li>filters</li></ul>
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
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From ef6539a1ff0125cbea87a0efdf970110096b59cc Mon Sep 17 00:00:00 2001
From: ehatzi <ehatzi@iti.gr>
Date: Fri, 25 Nov 2016 15:07:21 +0200
Subject: [PATCH 2/3] Added documentation

---
 .../CSPFilterBankWrapper.m                    | 184 ++++++++++++++++++
 exampleERRPSSVEPDemo.m                        |  46 +++++
 2 files changed, 230 insertions(+)
 create mode 100644 +eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
 create mode 100644 exampleERRPSSVEPDemo.m

diff --git a/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m b/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
new file mode 100644
index 0000000..97e9faf
--- /dev/null
+++ b/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
@@ -0,0 +1,184 @@
+classdef CSPFilterBankWrapper < eegtoolkit.classification.ClassifierBase;
+    properties (Constant)
+        
+    end
+    properties
+        baseClassifier;
+        channel;
+        cspFilters;
+        filterBanks;
+        samplingRate;
+    end
+    
+    methods (Access = public)
+        function CSPFB = CSPFilterBankWrapper(filterBanks, samplingRate)
+            CSPFB.cspFilters = {};
+            CSPFB.filterBanks = filterBanks;
+            CSPFB.samplingRate = samplingRate;
+            %filter_banks=[8 12; 12 16; 16 20;20 24;24 28];
+%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')
+%                 CSP.instanceSet = instanceSet;
+%             else
+%                 error('RawSignal extractor should be used with CSPWrapper');
+%             end
+        end
+        
+        
+        function CSPFB = build(CSPFB)
+            % Builds the classification models
+            CSPFB.learnCSPMatrix(CSPFB.instanceSet.sMatrix,CSPFB.instanceSet.labels);
+            instanceLocal = CSPFB.extract(CSPFB.instanceSet.sMatrix);
+            CSPFB.baseClassifier.instanceSet = eegtoolkit.util.InstanceSet(instanceLocal,CSPFB.instanceSet.labels);
+            CSPFB.baseClassifier.build;
+            CSPFB.reset;
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(CSPFB,instance)
+            
+%             instance = CSP.extract
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            testInstances = CSPFB.extract(instance);
+            [output, probabilities, ranking] = CSPFB.baseClassifier.classifyInstance(testInstances);
+%             numModels = length(LSVM.models);
+%             [numinstance, ~] = size(testInstances);
+%             scores = zeros(numModels,numinstance);
+%             for i=1:numModels
+%                 %predict using the stored models
+%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = t(:,1);
+%             end
+%             output = zeros(numinstance,1);
+%             probabilities = zeros(numinstance,1);
+%             ranking = scores;
+%             for i=1:numinstance
+%                 %select the class with the highest probability
+%                 [prob, idx] = max(scores(:,i));
+%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+%                 %output the label with highest probability
+%                 output(i,1) = uniqueLabels(idx);
+%                 %return the probability for the output label
+%                 probabilities(i,1) = prob;
+%             end
+        end
+        
+        function CSPFB = reset(CSPFB)
+            % 'Resets' the classifier.
+%             CSP.models = {};
+        end
+        
+        function configInfo = getConfigInfo(CSPFB)
+            configInfo = '\n';
+        end
+        
+                        
+        function time = getTime(CSPFB)
+            time = 0;
+        end
+    end
+    methods (Access = private)
+        function [] = learnCSPMatrix(CSPFB, sMatrix, labels)
+                       %[trialsMat,labels] = ssveptoolkit.util.Trial.trialsCellToMat(in);            
+            [numTrials,numChannels,numSamples] = size(sMatrix);
+%             numTrials = length(CSPFB.trials);
+%             [numChannels,numSamples] = size(CSPFB.trials{1}.signal);
+%             samplingRate = CSPFB.trials{1}.samplingRate;
+            filter_banks= CSPFB.filterBanks;
+            [nfb, mfb] = size(filter_banks);
+
+            for iter_fb=1:nfb
+                
+                [b,a]=butter(3,filter_banks(iter_fb)/(CSPFB.samplingRate/2));
+%                 labels = zeros(numTrials,1);
+                %numTrials X numChannels X numSamples
+                trialsMat = permute(sMatrix,[2,3,1]);
+%                 trialsMat = zeros(numChannels,numSamples,numTrials);
+%                 for i = 1 : length(CSP_Feat.trials)
+%                     for i_ch = 1:numChannels
+%                         trialsMat(i_ch,:,i) = filtfilt(b,a,CSP_Feat.trials{i}.signal(i_ch,:));
+%                     end
+%                     labels(i) = CSP_Feat.trials{i}.label;
+%                 end
+                
+                trialsMat = permute(trialsMat,[2 1 3]);
+                [N1, Nch1, Ntr1] = size(trialsMat);
+                for i = 1:Nch1
+                    for j = 1:Ntr1
+                        trialsMat(:,i,j) = (trialsMat(:,i,j) - mean(trialsMat(:,i,j)));
+                    end
+                end
+                x_train = trialsMat;%(:,:,CSP_Feat.trainIdx);
+                y_train = labels;%(CSP_Feat.trainIdx);
+                [N, Nch, Ntr] = size(x_train);
+                trialCov=zeros(Nch,Nch,Ntr);
+                for t=1:length(y_train)
+                    E = x_train(:,:,t)';
+                    EE = E * E';
+                    trialCov(:,:,t) = EE ./ trace(EE);
+                end
+                for c=1:2
+                    covMat{c} = mean(trialCov(:,:,y_train == c),3);
+                end
+                [U, D] = eig(covMat{1},covMat{2},'qz');
+                eigenvalues = diag(D);
+                [~, ind] = sort(eigenvalues, 'descend');
+                U = U(:,ind);
+                CSPFB.cspFilters{iter_fb} = U';
+%                 CSP_Filter = U';
+            end
+                %trialsMat2=zeros(N,3,Ntr);
+               
+        end
+        
+        function instances = extract(CSPFB,sMatrix)
+            trialsMat = permute(sMatrix,[2,3,1]);
+            trialsMat = permute(trialsMat,[2,1,3]);
+            [numTrials,numChannels,~] = size(sMatrix);
+            final_instances = zeros(numTrials, numChannels*length(CSPFB.filterBanks));
+            for iter_fb=1:length(CSPFB.cspFilters)
+                for j = 1:size(trialsMat,3)
+                    trialsMat(:,:,j) = (CSPFB.cspFilters{iter_fb}*trialsMat(:,:,j)')';
+                end
+                
+                instances = zeros(numTrials, numChannels);
+                %labels = zeros(numTrials,1);
+                
+                for i=1:numTrials
+                    
+                    projectedTrial = trialsMat(:,:,i);%Filter * CSP_Feat.trials{i}.signal(:,i);% EEGSignals.x(:,:,t)';
+                    %generating the features as the log variance of the projected signals
+                    variances = var(projectedTrial,0,1);
+                    instances(i,:) = log(variances)';
+                    %labels(i,1) = floor(CSP_Feat.trials{i}.label);
+                end
+                final_instances(:,numChannels*(iter_fb-1)+1:numChannels*iter_fb) = instances;
+                %            CSP_Feat.avgTime = toc/numTrials;
+%                 CSP_Feat.instanceSet = ssveptoolkit.util.InstanceSet(final_instances,labels);
+            end
+            instances = final_instances;
+        end
+    
+    
+    
+    end
+    %             [numTrials,numChannels,~] = size(sMatrix);
+    %             sMatrix = permute(sMatrix,[3,2,1]);
+    %             for i=1:size(sMatrix,3);
+    %                 sMatrix(:,:,i) = (CSPFB.cspFilter*sMatrix(:,:,i)')';
+    %             end
+    %             instances = zeros(numTrials,numChannels);
+    %             for i=1:numTrials
+    %                 projectedTrial = sMatrix(:,:,i);
+    %                 variances = var(projectedTrial,0,1);
+    %                 instances(i,:) = log(variances)';
+    %             end
+    % %             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+    %         end
+    %end
+end
+
diff --git a/exampleERRPSSVEPDemo.m b/exampleERRPSSVEPDemo.m
new file mode 100644
index 0000000..4bd172f
--- /dev/null
+++ b/exampleERRPSSVEPDemo.m
@@ -0,0 +1,46 @@
+% d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');
+
+sess = eegtoolkit.util.Session;
+sess.loadSubjectSession(8,5,2);
+
+[z,p,k]=butter(3,[1,10]/64);
+[s,g]=zp2sos(z,p,k);
+Hd = dfilt.df2sos(s,g);
+df = eegtoolkit.preprocessing.DigitalFilter; %
+df.filt = Hd;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.channels = [1:14];
+ss.sampleRange = [1:6:200];
+
+extr = {};
+for i=1:3
+    extr{i} = eegtoolkit.featextraction.PWelch;
+    extr{i}.channel = 1;
+end
+
+aggr = eegtoolkit.aggregation.ChannelConcat;
+
+classif = eegtoolkit.classification.LIBSVM;
+classif.kernel = classif.KERNEL_RBF;
+classif.gamma = 1/9;
+classif.cost = 1;
+
+%Setup experiment
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {df,ss};
+experiment.featextraction = extr;
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+
+experiment.run(10);
+
+accuracies = [];
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+fprintf('mean acc = %.2f\n',mean(accuracies));
\ No newline at end of file

From 812364c3313813bfc6c68495fea967049edc9e0e Mon Sep 17 00:00:00 2001
From: ehatzi <ehatzi@iti.gr>
Date: Fri, 25 Nov 2016 17:13:23 +0200
Subject: [PATCH 3/3] Updated documentation

---
 .../@ClassifierBase/ClassifierBase.m          |   2 +-
 .../FeatureExtractionBase.m                   |   3 +-
 .../@AggregatorBase/AggregatorBase.html       |   6 +-
 .../+aggregation/@AggregatorBase/graph.html   |  14 +-
 .../+aggregation/@AggregatorBase/index.html   |  12 +-
 .../@ChannelAveraging/ChannelAveraging.html   |   6 +-
 .../+aggregation/@ChannelAveraging/graph.html |  14 +-
 .../+aggregation/@ChannelAveraging/index.html |  12 +-
 .../@ChannelConcat/ChannelConcat.html         |   6 +-
 .../+aggregation/@ChannelConcat/graph.html    |  14 +-
 .../+aggregation/@ChannelConcat/index.html    |  12 +-
 .../@ChannelRatio/ChannelRatio.html           |   6 +-
 .../+aggregation/@ChannelRatio/graph.html     |  14 +-
 .../+aggregation/@ChannelRatio/index.html     |  12 +-
 .../+aggregation/@Fisher/Fisher.html          |   6 +-
 .../+aggregation/@Fisher/graph.html           |  14 +-
 .../+aggregation/@Fisher/index.html           |  12 +-
 .../+aggregation/@LateFusion/LateFusion.html  |   6 +-
 .../+aggregation/@LateFusion/graph.html       |  14 +-
 .../+aggregation/@LateFusion/index.html       |  12 +-
 doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html  |   6 +-
 doc/+eegtoolkit/+aggregation/@VLAD/graph.html |  14 +-
 doc/+eegtoolkit/+aggregation/@VLAD/index.html |  12 +-
 .../+classification/@Adaboost/Adaboost.html   |   6 +-
 .../+classification/@Adaboost/graph.html      |  14 +-
 .../+classification/@Adaboost/index.html      |  12 +-
 .../CSPFilterBankWrapper.html                 | 234 ++++++++++++++++++
 .../CSPFilterBankWrapper.m                    | 184 ++++++++++++++
 .../@CSPFilterBankWrapper/graph.dot           |   6 +
 .../@CSPFilterBankWrapper/graph.html          |  28 +++
 .../@CSPFilterBankWrapper/graph.map           |   1 +
 .../@CSPFilterBankWrapper/graph.png           | Bin 0 -> 7147 bytes
 .../@CSPFilterBankWrapper/index.html          |  32 +++
 .../@CSPWrapper/CSPWrapper.html               |   6 +-
 .../+classification/@CSPWrapper/graph.html    |  14 +-
 .../+classification/@CSPWrapper/index.html    |  12 +-
 .../@ClassifierBase/ClassifierBase.html       |  10 +-
 .../@ClassifierBase/ClassifierBase.m          |   2 +-
 .../@ClassifierBase/graph.html                |  14 +-
 .../@ClassifierBase/index.html                |  12 +-
 .../+classification/@CombiCCA/CombiCCA.html   |   6 +-
 .../+classification/@CombiCCA/graph.html      |  14 +-
 .../+classification/@CombiCCA/index.html      |  12 +-
 .../FusionClassifierWrapper.html              |   6 +-
 .../@FusionClassifierWrapper/graph.html       |  14 +-
 .../@FusionClassifierWrapper/index.html       |  12 +-
 .../+classification/@ITCCA/ITCCA.html         |   6 +-
 .../+classification/@ITCCA/graph.html         |  14 +-
 .../+classification/@ITCCA/index.html         |  12 +-
 .../+classification/@L1MCCA/L1MCCA.html       |   6 +-
 .../+classification/@L1MCCA/graph.html        |  14 +-
 .../+classification/@L1MCCA/index.html        |  12 +-
 doc/+eegtoolkit/+classification/@LDA/LDA.html |   6 +-
 .../+classification/@LDA/graph.html           |  14 +-
 .../+classification/@LDA/index.html           |  12 +-
 .../+classification/@LIBSVM/LIBSVM.html       |   6 +-
 .../+classification/@LIBSVM/graph.html        |  14 +-
 .../+classification/@LIBSVM/index.html        |  12 +-
 .../@LIBSVMFast/LIBSVMFast.html               |   6 +-
 .../+classification/@LIBSVMFast/graph.html    |  14 +-
 .../+classification/@LIBSVMFast/index.html    |  12 +-
 .../+classification/@MLDA/MLDA.html           |   6 +-
 .../+classification/@MLDA/graph.html          |  14 +-
 .../+classification/@MLDA/index.html          |  12 +-
 doc/+eegtoolkit/+classification/@MLR/MLR.html |   6 +-
 .../+classification/@MLR/graph.html           |  14 +-
 .../+classification/@MLR/index.html           |  12 +-
 .../+classification/@MLTREE/MLTREE.html       |   6 +-
 .../+classification/@MLTREE/graph.html        |  14 +-
 .../+classification/@MLTREE/index.html        |  12 +-
 .../@MLTboxMulticlass/MLTboxMulticlass.html   |   6 +-
 .../@MLTboxMulticlass/graph.html              |  14 +-
 .../@MLTboxMulticlass/index.html              |  12 +-
 .../@MaxChooser/MaxChooser.html               |   6 +-
 .../+classification/@MaxChooser/graph.html    |  14 +-
 .../+classification/@MaxChooser/index.html    |  12 +-
 .../+classification/@SBLR/SBLR.html           |   6 +-
 .../+classification/@SBLR/graph.html          |  14 +-
 .../+classification/@SBLR/index.html          |  12 +-
 .../+classification/@SMFA/SMFA.html           |   6 +-
 .../+classification/@SMFA/graph.html          |  14 +-
 .../+classification/@SMFA/index.html          |  12 +-
 .../@Experimenter/Experimenter.html           |   6 +-
 .../+experiment/@Experimenter/graph.html      |  14 +-
 .../+experiment/@Experimenter/index.html      |  12 +-
 .../@ResultEvaluator/ResultEvaluator.html     |   6 +-
 .../+experiment/@ResultEvaluator/graph.html   |  14 +-
 .../+experiment/@ResultEvaluator/index.html   |  12 +-
 doc/+eegtoolkit/+featextraction/@CCA/CCA.html |   6 +-
 .../+featextraction/@CCA/graph.html           |  14 +-
 .../+featextraction/@CCA/index.html           |  12 +-
 doc/+eegtoolkit/+featextraction/@DWT/DWT.html |   6 +-
 .../+featextraction/@DWT/graph.html           |  14 +-
 .../+featextraction/@DWT/index.html           |  12 +-
 .../@ERRPFeatures/ERRPFeatures.html           |   6 +-
 .../+featextraction/@ERRPFeatures/graph.html  |  14 +-
 .../+featextraction/@ERRPFeatures/index.html  |  12 +-
 doc/+eegtoolkit/+featextraction/@FFT/FFT.html |   6 +-
 .../+featextraction/@FFT/graph.html           |  14 +-
 .../+featextraction/@FFT/index.html           |  12 +-
 .../FeatureExtractionBase.html                | 142 ++++++-----
 .../FeatureExtractionBase.m                   |   3 +-
 .../@FeatureExtractionBase/graph.html         |  14 +-
 .../@FeatureExtractionBase/index.html         |  12 +-
 .../+featextraction/@Goertzel/Goertzel.html   |   6 +-
 .../+featextraction/@Goertzel/graph.html      |  14 +-
 .../+featextraction/@Goertzel/index.html      |  12 +-
 .../+featextraction/@L1MCCA/L1MCCA.html       |   6 +-
 .../+featextraction/@L1MCCA/graph.html        |  14 +-
 .../+featextraction/@L1MCCA/index.html        |  12 +-
 .../@MLR_Transf/MLR_Transf.html               |   6 +-
 .../+featextraction/@MLR_Transf/graph.html    |  14 +-
 .../+featextraction/@MLR_Transf/index.html    |  12 +-
 .../@PSDExtractionBase/PSDExtractionBase.html |   6 +-
 .../@PSDExtractionBase/graph.html             |  14 +-
 .../@PSDExtractionBase/index.html             |  12 +-
 .../+featextraction/@PWelch/PWelch.html       |   6 +-
 .../+featextraction/@PWelch/graph.html        |  14 +-
 .../+featextraction/@PWelch/index.html        |  12 +-
 .../PWelchExperimental.html                   |   6 +-
 .../@PWelchExperimental/graph.html            |  14 +-
 .../@PWelchExperimental/index.html            |  12 +-
 .../+featextraction/@PYAR/PYAR.html           |   6 +-
 .../+featextraction/@PYAR/graph.html          |  14 +-
 .../+featextraction/@PYAR/index.html          |  12 +-
 .../+featextraction/@RawSignal/RawSignal.html |   6 +-
 .../+featextraction/@RawSignal/graph.html     |  14 +-
 .../+featextraction/@RawSignal/index.html     |  12 +-
 .../+featextraction/@STFT/STFT.html           |   6 +-
 .../+featextraction/@STFT/graph.html          |  14 +-
 .../+featextraction/@STFT/index.html          |  12 +-
 .../+featselection/@FEAST/FEAST.html          |   6 +-
 .../+featselection/@FEAST/graph.html          |  14 +-
 .../+featselection/@FEAST/index.html          |  12 +-
 .../FeatureSelectionBase.html                 |   6 +-
 .../@FeatureSelectionBase/graph.html          |  14 +-
 .../@FeatureSelectionBase/index.html          |  12 +-
 doc/+eegtoolkit/+featselection/@PCA/PCA.html  |   6 +-
 .../+featselection/@PCA/graph.html            |  14 +-
 .../+featselection/@PCA/index.html            |  12 +-
 doc/+eegtoolkit/+featselection/@SVD/SVD.html  |   6 +-
 .../+featselection/@SVD/graph.html            |  14 +-
 .../+featselection/@SVD/index.html            |  12 +-
 .../+preprocessing/@Amuse/Amuse.html          |   6 +-
 .../+preprocessing/@Amuse/graph.html          |  14 +-
 .../+preprocessing/@Amuse/index.html          |  12 +-
 .../@DigitalFilter/DigitalFilter.html         |   6 +-
 .../+preprocessing/@DigitalFilter/graph.html  |  14 +-
 .../+preprocessing/@DigitalFilter/index.html  |  12 +-
 .../+preprocessing/@FastICA/FastICA.html      |   6 +-
 .../+preprocessing/@FastICA/graph.html        |  14 +-
 .../+preprocessing/@FastICA/index.html        |  12 +-
 .../@PreprocessingBase/PreprocessingBase.html |   6 +-
 .../@PreprocessingBase/graph.html             |  14 +-
 .../@PreprocessingBase/index.html             |  12 +-
 .../@Rereferencing/Rereferencing.html         |   6 +-
 .../+preprocessing/@Rereferencing/graph.html  |  14 +-
 .../+preprocessing/@Rereferencing/index.html  |  12 +-
 .../@SampleSelection/SampleSelection.html     |   6 +-
 .../@SampleSelection/graph.html               |  14 +-
 .../@SampleSelection/index.html               |  12 +-
 .../@Windsorize/Windsorize.html               |   6 +-
 .../+preprocessing/@Windsorize/graph.html     |  14 +-
 .../+preprocessing/@Windsorize/index.html     |  12 +-
 .../@FusionInstanceSet/FusionInstanceSet.html |   6 +-
 .../+util/@FusionInstanceSet/graph.html       |  14 +-
 .../+util/@FusionInstanceSet/index.html       |  12 +-
 .../+util/@InstanceSet/InstanceSet.html       |   6 +-
 doc/+eegtoolkit/+util/@InstanceSet/graph.html |  14 +-
 doc/+eegtoolkit/+util/@InstanceSet/index.html |  12 +-
 .../@L1MCCAInstanceSet/L1MCCAInstanceSet.html |   6 +-
 .../+util/@L1MCCAInstanceSet/graph.html       |  14 +-
 .../+util/@L1MCCAInstanceSet/index.html       |  12 +-
 .../+util/@LSLWrapper/LSLWrapper.html         |   6 +-
 doc/+eegtoolkit/+util/@LSLWrapper/graph.html  |  14 +-
 doc/+eegtoolkit/+util/@LSLWrapper/index.html  |  12 +-
 .../+util/@RawSignalSet/RawSignalSet.html     |   6 +-
 .../+util/@RawSignalSet/graph.html            |  14 +-
 .../+util/@RawSignalSet/index.html            |  12 +-
 .../+util/@ResultSet/ResultSet.html           |   6 +-
 doc/+eegtoolkit/+util/@ResultSet/graph.html   |  14 +-
 doc/+eegtoolkit/+util/@ResultSet/index.html   |  12 +-
 doc/+eegtoolkit/+util/@Session/Session.html   |   6 +-
 doc/+eegtoolkit/+util/@Session/graph.html     |  14 +-
 doc/+eegtoolkit/+util/@Session/index.html     |  12 +-
 doc/+eegtoolkit/+util/@Trial/Trial.html       |   6 +-
 doc/+eegtoolkit/+util/@Trial/graph.html       |  14 +-
 doc/+eegtoolkit/+util/@Trial/index.html       |  12 +-
 doc/exampleCSP.html                           |   2 +-
 doc/exampleCombiCCA.html                      |   2 +-
 doc/exampleDefault.html                       |   2 +-
 doc/exampleEPOCCCASVM.html                    |   2 +-
 doc/exampleERRP.html                          |   2 +-
 doc/exampleERRPSSVEPDemo.html                 |  94 +++++++
 doc/exampleERRPSSVEPDemo.m                    |  46 ++++
 doc/exampleEarlyFusion.html                   |   2 +-
 doc/exampleEpoc.html                          |   2 +-
 doc/exampleITCCA.html                         |   2 +-
 doc/exampleL1MCCA.html                        |   2 +-
 doc/exampleLSL.html                           |   2 +-
 doc/exampleLateFusion.html                    |   2 +-
 doc/exampleMotorPWelch.html                   |   2 +-
 doc/exampleOptimal.html                       |   2 +-
 doc/exampleSMFA.html                          |   2 +-
 doc/graph.dot                                 |   1 +
 doc/graph.html                                |  21 +-
 doc/graph.map                                 |  19 +-
 doc/graph.png                                 | Bin 45456 -> 49050 bytes
 doc/index.html                                |   4 +-
 209 files changed, 1680 insertions(+), 1056 deletions(-)
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.html
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.dot
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.html
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.map
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.png
 create mode 100644 doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/index.html
 create mode 100644 doc/exampleERRPSSVEPDemo.html
 create mode 100644 doc/exampleERRPSSVEPDemo.m

diff --git a/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m b/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
index ad07e26..531957d 100644
--- a/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
+++ b/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
@@ -1,5 +1,5 @@
 % Abstract class for classification. Implement the functions for any
-% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+% classifier (e.g. LibSVM, LDA, MLR, RFs, Adaboost, etc.)
 % 
 % Properties:
 % instanceSet: the training/test set in an InstanceSet structure
diff --git a/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m b/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
index 29ef454..647966b 100644
--- a/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
+++ b/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
@@ -1,6 +1,5 @@
 % Abstract class for feature extraction. Implement the functions for any
-% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
-% rereferencing, etc.
+% feature extractor (e.g. PWelch, FFT, DWT, PYAR, etc.)
 % 
 % Properties:
 % instanceSet: Output - the features in an InstanceSet structure
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html
index c987680..f4dcd71 100644
--- a/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/AggregatorBase.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@AggregatorBase</a> &gt; AggregatorBase.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@AggregatorBase</a> &gt; AggregatorBase.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>AggregatorBase
 </h1>
@@ -96,6 +96,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0033     
 0034 <span class="keyword">end</span>
 0035</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html
index 63f8728..4fd7b72 100644
--- a/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html
+++ b/doc/+eegtoolkit/+aggregation/@AggregatorBase/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@AggregatorBase">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@AggregatorBase">
+  <title>Dependency Graph for +eegtoolkit/+aggregation/@AggregatorBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+aggregation/@AggregatorBase">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+aggregation/@AggregatorBase">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+aggregation/@AggregatorBase</h1>
 
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-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@AggregatorBase" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+aggregation/@AggregatorBase" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@AggregatorBase/index.html b/doc/+eegtoolkit/+aggregation/@AggregatorBase/index.html
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-  <meta name="keywords" content="./+eegtoolkit/+aggregation/@AggregatorBase">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@AggregatorBase">
+  <title>Index for Directory +eegtoolkit/+aggregation/@AggregatorBase</title>
+  <meta name="keywords" content="+eegtoolkit/+aggregation/@AggregatorBase">
+  <meta name="description" content="Index for Directory +eegtoolkit/+aggregation/@AggregatorBase">
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@AggregatorBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@AggregatorBase</h1>
+<h1>Index for +eegtoolkit/+aggregation/@AggregatorBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html
index 7725575..663856b 100644
--- a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html
+++ b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/ChannelAveraging.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelAveraging</a> &gt; ChannelAveraging.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@ChannelAveraging</a> &gt; ChannelAveraging.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ChannelAveraging
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 0031     
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <title>Dependency Graph for +eegtoolkit/+aggregation/@ChannelAveraging</title>
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+  <meta name="description" content="Dependency graph for +eegtoolkit/+aggregation/@ChannelAveraging">
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-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelAveraging</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+aggregation/@ChannelAveraging</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelAveraging" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+aggregation/@ChannelAveraging" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelAveraging/index.html b/doc/+eegtoolkit/+aggregation/@ChannelAveraging/index.html
index 43b615a..0ba6bd3 100644
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@ChannelAveraging">
+  <title>Index for Directory +eegtoolkit/+aggregation/@ChannelAveraging</title>
+  <meta name="keywords" content="+eegtoolkit/+aggregation/@ChannelAveraging">
+  <meta name="description" content="Index for Directory +eegtoolkit/+aggregation/@ChannelAveraging">
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelAveraging&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@ChannelAveraging</h1>
+<h1>Index for +eegtoolkit/+aggregation/@ChannelAveraging</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html
index 6e777be..10b2ede 100644
--- a/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html
+++ b/doc/+eegtoolkit/+aggregation/@ChannelConcat/ChannelConcat.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelConcat</a> &gt; ChannelConcat.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@ChannelConcat</a> &gt; ChannelConcat.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ChannelConcat
 </h1>
@@ -79,6 +79,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0032     
 0033 <span class="keyword">end</span>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.html
index 307459e..c193196 100644
--- a/doc/+eegtoolkit/+aggregation/@ChannelConcat/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+aggregation/@ChannelConcat">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelConcat">
+  <title>Dependency Graph for +eegtoolkit/+aggregation/@ChannelConcat</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+aggregation/@ChannelConcat">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+aggregation/@ChannelConcat">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelConcat</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+aggregation/@ChannelConcat</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelConcat" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelConcat/index.html b/doc/+eegtoolkit/+aggregation/@ChannelConcat/index.html
index 1460814..35ef929 100644
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-  <meta name="keywords" content="./+eegtoolkit/+aggregation/@ChannelConcat">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@ChannelConcat">
+  <title>Index for Directory +eegtoolkit/+aggregation/@ChannelConcat</title>
+  <meta name="keywords" content="+eegtoolkit/+aggregation/@ChannelConcat">
+  <meta name="description" content="Index for Directory +eegtoolkit/+aggregation/@ChannelConcat">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelConcat&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@ChannelConcat</h1>
+<h1>Index for +eegtoolkit/+aggregation/@ChannelConcat</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html
index e649cb2..a4fb8e1 100644
--- a/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html
+++ b/doc/+eegtoolkit/+aggregation/@ChannelRatio/ChannelRatio.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@ChannelRatio</a> &gt; ChannelRatio.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@ChannelRatio</a> &gt; ChannelRatio.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ChannelRatio
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+aggregation/@ChannelRatio">
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+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+aggregation/@ChannelRatio">
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-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelRatio</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+aggregation/@ChannelRatio</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@ChannelRatio" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@ChannelRatio/index.html b/doc/+eegtoolkit/+aggregation/@ChannelRatio/index.html
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+  <title>Index for Directory +eegtoolkit/+aggregation/@ChannelRatio</title>
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@ChannelRatio&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@ChannelRatio</h1>
+<h1>Index for +eegtoolkit/+aggregation/@ChannelRatio</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.html b/doc/+eegtoolkit/+aggregation/@Fisher/Fisher.html
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@@ -12,10 +12,10 @@
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@Fisher</a> &gt; Fisher.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@Fisher</a> &gt; Fisher.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Fisher
 </h1>
@@ -142,6 +142,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0095     
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@Fisher/graph.html b/doc/+eegtoolkit/+aggregation/@Fisher/graph.html
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-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@Fisher</h1>
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 <center>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@Fisher&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@Fisher</h1>
+<h1>Index for +eegtoolkit/+aggregation/@Fisher</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.html b/doc/+eegtoolkit/+aggregation/@LateFusion/LateFusion.html
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@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@LateFusion</a> &gt; LateFusion.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@LateFusion</a> &gt; LateFusion.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>LateFusion
 </h1>
@@ -76,6 +76,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0029     
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/graph.html b/doc/+eegtoolkit/+aggregation/@LateFusion/graph.html
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-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@LateFusion</h1>
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 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+aggregation/@LateFusion" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@LateFusion/index.html b/doc/+eegtoolkit/+aggregation/@LateFusion/index.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@LateFusion&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@LateFusion</h1>
+<h1>Index for +eegtoolkit/+aggregation/@LateFusion</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html b/doc/+eegtoolkit/+aggregation/@VLAD/VLAD.html
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@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="#">@VLAD</a> &gt; VLAD.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+aggregation</a> &gt; <a href="index.html">@VLAD</a> &gt; VLAD.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>VLAD
 </h1>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/graph.html b/doc/+eegtoolkit/+aggregation/@VLAD/graph.html
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-<h1>Dependency Graph for ./+eegtoolkit/+aggregation/@VLAD</h1>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+aggregation/@VLAD/index.html b/doc/+eegtoolkit/+aggregation/@VLAD/index.html
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 <head>
-  <title>Index for Directory ./+eegtoolkit/+aggregation/@VLAD</title>
-  <meta name="keywords" content="./+eegtoolkit/+aggregation/@VLAD">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+aggregation/@VLAD">
+  <title>Index for Directory +eegtoolkit/+aggregation/@VLAD</title>
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@@ -13,9 +13,9 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+aggregation/@VLAD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+aggregation/@VLAD</h1>
+<h1>Index for +eegtoolkit/+aggregation/@VLAD</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html
index 27f3d17..77e9e11 100644
--- a/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html
+++ b/doc/+eegtoolkit/+classification/@Adaboost/Adaboost.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@Adaboost</a> &gt; Adaboost.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@Adaboost</a> &gt; Adaboost.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Adaboost
 </h1>
@@ -176,6 +176,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0129     <span class="keyword">end</span>
 0130 <span class="keyword">end</span>
 0131</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
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diff --git a/doc/+eegtoolkit/+classification/@Adaboost/graph.html b/doc/+eegtoolkit/+classification/@Adaboost/graph.html
index 3ed3a88..abc259f 100644
--- a/doc/+eegtoolkit/+classification/@Adaboost/graph.html
+++ b/doc/+eegtoolkit/+classification/@Adaboost/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+classification/@Adaboost</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@Adaboost">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@Adaboost">
+  <title>Dependency Graph for +eegtoolkit/+classification/@Adaboost</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@Adaboost">
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@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+classification/@Adaboost</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@Adaboost</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@Adaboost" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@Adaboost" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="Adaboost.html" title="Adaboost" alt="" coords="123,29,120,22,112,15,99,10,82,7,64,5,46,7,29,10,16,15,8,22,5,29,8,37,16,43,29,49,46,52,64,53,82,52,99,49,112,43,120,37">
 </map> 
 </center>
 
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@Adaboost/index.html b/doc/+eegtoolkit/+classification/@Adaboost/index.html
index 85d8290..8cf6af8 100644
--- a/doc/+eegtoolkit/+classification/@Adaboost/index.html
+++ b/doc/+eegtoolkit/+classification/@Adaboost/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+classification/@Adaboost</title>
-  <meta name="keywords" content="./+eegtoolkit/+classification/@Adaboost">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@Adaboost">
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@@ -13,9 +13,9 @@
 <body>
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@Adaboost&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@Adaboost</h1>
+<h1>Index for +eegtoolkit/+classification/@Adaboost</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.html b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.html
new file mode 100644
index 0000000..83519fa
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.html
@@ -0,0 +1,234 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of CSPFilterBankWrapper</title>
+  <meta name="keywords" content="CSPFilterBankWrapper">
+  <meta name="description" content="">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@CSPFilterBankWrapper</a> &gt; CSPFilterBankWrapper.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPFilterBankWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+
+<h1>CSPFilterBankWrapper
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong></strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre class="comment"></pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CSPFilterBankWrapper.html" class="code" title="">CSPFilterBankWrapper</a>	</li></ul>
+This function is called by:
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="CSPFilterBankWrapper.html" class="code" title="">CSPFilterBankWrapper</a>	</li></ul>
+<!-- crossreference -->
+
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<ul style="list-style-image:url(../../../matlabicon.gif)">
+<li><a href="#_sub1" class="code">function CSPFB = CSPFilterBankWrapper(filterBanks, samplingRate)</a></li><li><a href="#_sub2" class="code">function CSPFB = build(CSPFB)</a></li><li><a href="#_sub3" class="code">function [output, probabilities, ranking] = classifyInstance(CSPFB,instance)</a></li><li><a href="#_sub4" class="code">function CSPFB = reset(CSPFB)</a></li><li><a href="#_sub5" class="code">function configInfo = getConfigInfo(CSPFB)</a></li><li><a href="#_sub6" class="code">function time = getTime(CSPFB)</a></li><li><a href="#_sub7" class="code">function [] = learnCSPMatrix(CSPFB, sMatrix, labels)</a></li><li><a href="#_sub8" class="code">function instances = extract(CSPFB,sMatrix)</a></li></ul>
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<p><a href="CSPFilterBankWrapper.m">CSPFilterBankWrapper.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
+<div class="fragment"><pre>0001 classdef <a href="CSPFilterBankWrapper.html" class="code" title="">CSPFilterBankWrapper</a> &lt; eegtoolkit.classification.ClassifierBase;
+0002     properties (Constant)
+0003         
+0004     <span class="keyword">end</span>
+0005     properties
+0006         baseClassifier;
+0007         channel;
+0008         cspFilters;
+0009         filterBanks;
+0010         samplingRate;
+0011     <span class="keyword">end</span>
+0012     
+0013     methods (Access = public)
+0014         <a name="_sub0" href="#_subfunctions" class="code">function CSPFB = CSPFilterBankWrapper(filterBanks, samplingRate)</a>
+0015             CSPFB.cspFilters = {};
+0016             CSPFB.filterBanks = filterBanks;
+0017             CSPFB.samplingRate = samplingRate;
+0018             <span class="comment">%filter_banks=[8 12; 12 16; 16 20;20 24;24 28];</span>
+0019 <span class="comment">%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')</span>
+0020 <span class="comment">%                 CSP.instanceSet = instanceSet;</span>
+0021 <span class="comment">%             else</span>
+0022 <span class="comment">%                 error('RawSignal extractor should be used with CSPWrapper');</span>
+0023 <span class="comment">%             end</span>
+0024         <span class="keyword">end</span>
+0025         
+0026         
+0027         <a name="_sub1" href="#_subfunctions" class="code">function CSPFB = build(CSPFB)</a>
+0028             <span class="comment">% Builds the classification models</span>
+0029             CSPFB.learnCSPMatrix(CSPFB.instanceSet.sMatrix,CSPFB.instanceSet.labels);
+0030             instanceLocal = CSPFB.extract(CSPFB.instanceSet.sMatrix);
+0031             CSPFB.baseClassifier.instanceSet = eegtoolkit.util.InstanceSet(instanceLocal,CSPFB.instanceSet.labels);
+0032             CSPFB.baseClassifier.build;
+0033             CSPFB.reset;
+0034         <span class="keyword">end</span>
+0035         
+0036         <a name="_sub2" href="#_subfunctions" class="code">function [output, probabilities, ranking] = classifyInstance(CSPFB,instance)</a>
+0037             
+0038 <span class="comment">%             instance = CSP.extract</span>
+0039             <span class="comment">%input = instance matrix rows = instances, cols = attributes</span>
+0040             <span class="comment">%output = predicted class</span>
+0041             <span class="comment">%probabilities = probability for predicted class</span>
+0042             <span class="comment">%ranking = propabilities for all classes (e.g. to use with mAP)</span>
+0043             
+0044             <span class="comment">%TODO:should print an error if 'build' has not been called</span>
+0045             testInstances = CSPFB.extract(instance);
+0046             [output, probabilities, ranking] = CSPFB.baseClassifier.classifyInstance(testInstances);
+0047 <span class="comment">%             numModels = length(LSVM.models);</span>
+0048 <span class="comment">%             [numinstance, ~] = size(testInstances);</span>
+0049 <span class="comment">%             scores = zeros(numModels,numinstance);</span>
+0050 <span class="comment">%             for i=1:numModels</span>
+0051 <span class="comment">%                 %predict using the stored models</span>
+0052 <span class="comment">%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');</span>
+0053 <span class="comment">%                 %store probability for each class</span>
+0054 <span class="comment">%                 scores(i,:) = t(:,1);</span>
+0055 <span class="comment">%             end</span>
+0056 <span class="comment">%             output = zeros(numinstance,1);</span>
+0057 <span class="comment">%             probabilities = zeros(numinstance,1);</span>
+0058 <span class="comment">%             ranking = scores;</span>
+0059 <span class="comment">%             for i=1:numinstance</span>
+0060 <span class="comment">%                 %select the class with the highest probability</span>
+0061 <span class="comment">%                 [prob, idx] = max(scores(:,i));</span>
+0062 <span class="comment">%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);</span>
+0063 <span class="comment">%                 %output the label with highest probability</span>
+0064 <span class="comment">%                 output(i,1) = uniqueLabels(idx);</span>
+0065 <span class="comment">%                 %return the probability for the output label</span>
+0066 <span class="comment">%                 probabilities(i,1) = prob;</span>
+0067 <span class="comment">%             end</span>
+0068         <span class="keyword">end</span>
+0069         
+0070         <a name="_sub3" href="#_subfunctions" class="code">function CSPFB = reset(CSPFB)</a>
+0071             <span class="comment">% 'Resets' the classifier.</span>
+0072 <span class="comment">%             CSP.models = {};</span>
+0073         <span class="keyword">end</span>
+0074         
+0075         <a name="_sub4" href="#_subfunctions" class="code">function configInfo = getConfigInfo(CSPFB)</a>
+0076             configInfo = <span class="string">'\n'</span>;
+0077         <span class="keyword">end</span>
+0078         
+0079                         
+0080         <a name="_sub5" href="#_subfunctions" class="code">function time = getTime(CSPFB)</a>
+0081             time = 0;
+0082         <span class="keyword">end</span>
+0083     <span class="keyword">end</span>
+0084     methods (Access = private)
+0085         <a name="_sub6" href="#_subfunctions" class="code">function [] = learnCSPMatrix(CSPFB, sMatrix, labels)</a>
+0086                        <span class="comment">%[trialsMat,labels] = ssveptoolkit.util.Trial.trialsCellToMat(in);</span>
+0087             [numTrials,numChannels,numSamples] = size(sMatrix);
+0088 <span class="comment">%             numTrials = length(CSPFB.trials);</span>
+0089 <span class="comment">%             [numChannels,numSamples] = size(CSPFB.trials{1}.signal);</span>
+0090 <span class="comment">%             samplingRate = CSPFB.trials{1}.samplingRate;</span>
+0091             filter_banks= CSPFB.filterBanks;
+0092             [nfb, mfb] = size(filter_banks);
+0093 
+0094             <span class="keyword">for</span> iter_fb=1:nfb
+0095                 
+0096                 [b,a]=butter(3,filter_banks(iter_fb)/(CSPFB.samplingRate/2));
+0097 <span class="comment">%                 labels = zeros(numTrials,1);</span>
+0098                 <span class="comment">%numTrials X numChannels X numSamples</span>
+0099                 trialsMat = permute(sMatrix,[2,3,1]);
+0100 <span class="comment">%                 trialsMat = zeros(numChannels,numSamples,numTrials);</span>
+0101 <span class="comment">%                 for i = 1 : length(CSP_Feat.trials)</span>
+0102 <span class="comment">%                     for i_ch = 1:numChannels</span>
+0103 <span class="comment">%                         trialsMat(i_ch,:,i) = filtfilt(b,a,CSP_Feat.trials{i}.signal(i_ch,:));</span>
+0104 <span class="comment">%                     end</span>
+0105 <span class="comment">%                     labels(i) = CSP_Feat.trials{i}.label;</span>
+0106 <span class="comment">%                 end</span>
+0107                 
+0108                 trialsMat = permute(trialsMat,[2 1 3]);
+0109                 [N1, Nch1, Ntr1] = size(trialsMat);
+0110                 <span class="keyword">for</span> i = 1:Nch1
+0111                     <span class="keyword">for</span> j = 1:Ntr1
+0112                         trialsMat(:,i,j) = (trialsMat(:,i,j) - mean(trialsMat(:,i,j)));
+0113                     <span class="keyword">end</span>
+0114                 <span class="keyword">end</span>
+0115                 x_train = trialsMat;<span class="comment">%(:,:,CSP_Feat.trainIdx);</span>
+0116                 y_train = labels;<span class="comment">%(CSP_Feat.trainIdx);</span>
+0117                 [N, Nch, Ntr] = size(x_train);
+0118                 trialCov=zeros(Nch,Nch,Ntr);
+0119                 <span class="keyword">for</span> t=1:length(y_train)
+0120                     E = x_train(:,:,t)';
+0121                     EE = E * E';
+0122                     trialCov(:,:,t) = EE ./ trace(EE);
+0123                 <span class="keyword">end</span>
+0124                 <span class="keyword">for</span> c=1:2
+0125                     covMat{c} = mean(trialCov(:,:,y_train == c),3);
+0126                 <span class="keyword">end</span>
+0127                 [U, D] = eig(covMat{1},covMat{2},<span class="string">'qz'</span>);
+0128                 eigenvalues = diag(D);
+0129                 [~, ind] = sort(eigenvalues, <span class="string">'descend'</span>);
+0130                 U = U(:,ind);
+0131                 CSPFB.cspFilters{iter_fb} = U';
+0132 <span class="comment">%                 CSP_Filter = U';</span>
+0133             <span class="keyword">end</span>
+0134                 <span class="comment">%trialsMat2=zeros(N,3,Ntr);</span>
+0135                
+0136         <span class="keyword">end</span>
+0137         
+0138         <a name="_sub7" href="#_subfunctions" class="code">function instances = extract(CSPFB,sMatrix)</a>
+0139             trialsMat = permute(sMatrix,[2,3,1]);
+0140             trialsMat = permute(trialsMat,[2,1,3]);
+0141             [numTrials,numChannels,~] = size(sMatrix);
+0142             final_instances = zeros(numTrials, numChannels*length(CSPFB.filterBanks));
+0143             <span class="keyword">for</span> iter_fb=1:length(CSPFB.cspFilters)
+0144                 <span class="keyword">for</span> j = 1:size(trialsMat,3)
+0145                     trialsMat(:,:,j) = (CSPFB.cspFilters{iter_fb}*trialsMat(:,:,j)')';
+0146                 <span class="keyword">end</span>
+0147                 
+0148                 instances = zeros(numTrials, numChannels);
+0149                 <span class="comment">%labels = zeros(numTrials,1);</span>
+0150                 
+0151                 <span class="keyword">for</span> i=1:numTrials
+0152                     
+0153                     projectedTrial = trialsMat(:,:,i);<span class="comment">%Filter * CSP_Feat.trials{i}.signal(:,i);% EEGSignals.x(:,:,t)';</span>
+0154                     <span class="comment">%generating the features as the log variance of the projected signals</span>
+0155                     variances = var(projectedTrial,0,1);
+0156                     instances(i,:) = log(variances)';
+0157                     <span class="comment">%labels(i,1) = floor(CSP_Feat.trials{i}.label);</span>
+0158                 <span class="keyword">end</span>
+0159                 final_instances(:,numChannels*(iter_fb-1)+1:numChannels*iter_fb) = instances;
+0160                 <span class="comment">%            CSP_Feat.avgTime = toc/numTrials;</span>
+0161 <span class="comment">%                 CSP_Feat.instanceSet = ssveptoolkit.util.InstanceSet(final_instances,labels);</span>
+0162             <span class="keyword">end</span>
+0163             instances = final_instances;
+0164         <span class="keyword">end</span>
+0165     
+0166     
+0167     
+0168     <span class="keyword">end</span>
+0169     <span class="comment">%             [numTrials,numChannels,~] = size(sMatrix);</span>
+0170     <span class="comment">%             sMatrix = permute(sMatrix,[3,2,1]);</span>
+0171     <span class="comment">%             for i=1:size(sMatrix,3);</span>
+0172     <span class="comment">%                 sMatrix(:,:,i) = (CSPFB.cspFilter*sMatrix(:,:,i)')';</span>
+0173     <span class="comment">%             end</span>
+0174     <span class="comment">%             instances = zeros(numTrials,numChannels);</span>
+0175     <span class="comment">%             for i=1:numTrials</span>
+0176     <span class="comment">%                 projectedTrial = sMatrix(:,:,i);</span>
+0177     <span class="comment">%                 variances = var(projectedTrial,0,1);</span>
+0178     <span class="comment">%                 instances(i,:) = log(variances)';</span>
+0179     <span class="comment">%             end</span>
+0180     <span class="comment">% %             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);</span>
+0181     <span class="comment">%         end</span>
+0182     <span class="comment">%end</span>
+0183 <span class="keyword">end</span>
+0184</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
new file mode 100644
index 0000000..97e9faf
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/CSPFilterBankWrapper.m
@@ -0,0 +1,184 @@
+classdef CSPFilterBankWrapper < eegtoolkit.classification.ClassifierBase;
+    properties (Constant)
+        
+    end
+    properties
+        baseClassifier;
+        channel;
+        cspFilters;
+        filterBanks;
+        samplingRate;
+    end
+    
+    methods (Access = public)
+        function CSPFB = CSPFilterBankWrapper(filterBanks, samplingRate)
+            CSPFB.cspFilters = {};
+            CSPFB.filterBanks = filterBanks;
+            CSPFB.samplingRate = samplingRate;
+            %filter_banks=[8 12; 12 16; 16 20;20 24;24 28];
+%             if(isa(instanceSet,'eegtoolkit.util.RawSignalSet')
+%                 CSP.instanceSet = instanceSet;
+%             else
+%                 error('RawSignal extractor should be used with CSPWrapper');
+%             end
+        end
+        
+        
+        function CSPFB = build(CSPFB)
+            % Builds the classification models
+            CSPFB.learnCSPMatrix(CSPFB.instanceSet.sMatrix,CSPFB.instanceSet.labels);
+            instanceLocal = CSPFB.extract(CSPFB.instanceSet.sMatrix);
+            CSPFB.baseClassifier.instanceSet = eegtoolkit.util.InstanceSet(instanceLocal,CSPFB.instanceSet.labels);
+            CSPFB.baseClassifier.build;
+            CSPFB.reset;
+        end
+        
+        function [output, probabilities, ranking] = classifyInstance(CSPFB,instance)
+            
+%             instance = CSP.extract
+            %input = instance matrix rows = instances, cols = attributes
+            %output = predicted class
+            %probabilities = probability for predicted class
+            %ranking = propabilities for all classes (e.g. to use with mAP)
+            
+            %TODO:should print an error if 'build' has not been called
+            testInstances = CSPFB.extract(instance);
+            [output, probabilities, ranking] = CSPFB.baseClassifier.classifyInstance(testInstances);
+%             numModels = length(LSVM.models);
+%             [numinstance, ~] = size(testInstances);
+%             scores = zeros(numModels,numinstance);
+%             for i=1:numModels
+%                 %predict using the stored models
+%                 [~, ~, t] = svmpredict(eye(numinstance,1),testInstances, LSVM.models{i},'-b 1 -q');
+%                 %store probability for each class
+%                 scores(i,:) = t(:,1);
+%             end
+%             output = zeros(numinstance,1);
+%             probabilities = zeros(numinstance,1);
+%             ranking = scores;
+%             for i=1:numinstance
+%                 %select the class with the highest probability
+%                 [prob, idx] = max(scores(:,i));
+%                 uniqueLabels = unique(LSVM.instanceSet.getLabels);
+%                 %output the label with highest probability
+%                 output(i,1) = uniqueLabels(idx);
+%                 %return the probability for the output label
+%                 probabilities(i,1) = prob;
+%             end
+        end
+        
+        function CSPFB = reset(CSPFB)
+            % 'Resets' the classifier.
+%             CSP.models = {};
+        end
+        
+        function configInfo = getConfigInfo(CSPFB)
+            configInfo = '\n';
+        end
+        
+                        
+        function time = getTime(CSPFB)
+            time = 0;
+        end
+    end
+    methods (Access = private)
+        function [] = learnCSPMatrix(CSPFB, sMatrix, labels)
+                       %[trialsMat,labels] = ssveptoolkit.util.Trial.trialsCellToMat(in);            
+            [numTrials,numChannels,numSamples] = size(sMatrix);
+%             numTrials = length(CSPFB.trials);
+%             [numChannels,numSamples] = size(CSPFB.trials{1}.signal);
+%             samplingRate = CSPFB.trials{1}.samplingRate;
+            filter_banks= CSPFB.filterBanks;
+            [nfb, mfb] = size(filter_banks);
+
+            for iter_fb=1:nfb
+                
+                [b,a]=butter(3,filter_banks(iter_fb)/(CSPFB.samplingRate/2));
+%                 labels = zeros(numTrials,1);
+                %numTrials X numChannels X numSamples
+                trialsMat = permute(sMatrix,[2,3,1]);
+%                 trialsMat = zeros(numChannels,numSamples,numTrials);
+%                 for i = 1 : length(CSP_Feat.trials)
+%                     for i_ch = 1:numChannels
+%                         trialsMat(i_ch,:,i) = filtfilt(b,a,CSP_Feat.trials{i}.signal(i_ch,:));
+%                     end
+%                     labels(i) = CSP_Feat.trials{i}.label;
+%                 end
+                
+                trialsMat = permute(trialsMat,[2 1 3]);
+                [N1, Nch1, Ntr1] = size(trialsMat);
+                for i = 1:Nch1
+                    for j = 1:Ntr1
+                        trialsMat(:,i,j) = (trialsMat(:,i,j) - mean(trialsMat(:,i,j)));
+                    end
+                end
+                x_train = trialsMat;%(:,:,CSP_Feat.trainIdx);
+                y_train = labels;%(CSP_Feat.trainIdx);
+                [N, Nch, Ntr] = size(x_train);
+                trialCov=zeros(Nch,Nch,Ntr);
+                for t=1:length(y_train)
+                    E = x_train(:,:,t)';
+                    EE = E * E';
+                    trialCov(:,:,t) = EE ./ trace(EE);
+                end
+                for c=1:2
+                    covMat{c} = mean(trialCov(:,:,y_train == c),3);
+                end
+                [U, D] = eig(covMat{1},covMat{2},'qz');
+                eigenvalues = diag(D);
+                [~, ind] = sort(eigenvalues, 'descend');
+                U = U(:,ind);
+                CSPFB.cspFilters{iter_fb} = U';
+%                 CSP_Filter = U';
+            end
+                %trialsMat2=zeros(N,3,Ntr);
+               
+        end
+        
+        function instances = extract(CSPFB,sMatrix)
+            trialsMat = permute(sMatrix,[2,3,1]);
+            trialsMat = permute(trialsMat,[2,1,3]);
+            [numTrials,numChannels,~] = size(sMatrix);
+            final_instances = zeros(numTrials, numChannels*length(CSPFB.filterBanks));
+            for iter_fb=1:length(CSPFB.cspFilters)
+                for j = 1:size(trialsMat,3)
+                    trialsMat(:,:,j) = (CSPFB.cspFilters{iter_fb}*trialsMat(:,:,j)')';
+                end
+                
+                instances = zeros(numTrials, numChannels);
+                %labels = zeros(numTrials,1);
+                
+                for i=1:numTrials
+                    
+                    projectedTrial = trialsMat(:,:,i);%Filter * CSP_Feat.trials{i}.signal(:,i);% EEGSignals.x(:,:,t)';
+                    %generating the features as the log variance of the projected signals
+                    variances = var(projectedTrial,0,1);
+                    instances(i,:) = log(variances)';
+                    %labels(i,1) = floor(CSP_Feat.trials{i}.label);
+                end
+                final_instances(:,numChannels*(iter_fb-1)+1:numChannels*iter_fb) = instances;
+                %            CSP_Feat.avgTime = toc/numTrials;
+%                 CSP_Feat.instanceSet = ssveptoolkit.util.InstanceSet(final_instances,labels);
+            end
+            instances = final_instances;
+        end
+    
+    
+    
+    end
+    %             [numTrials,numChannels,~] = size(sMatrix);
+    %             sMatrix = permute(sMatrix,[3,2,1]);
+    %             for i=1:size(sMatrix,3);
+    %                 sMatrix(:,:,i) = (CSPFB.cspFilter*sMatrix(:,:,i)')';
+    %             end
+    %             instances = zeros(numTrials,numChannels);
+    %             for i=1:numTrials
+    %                 projectedTrial = sMatrix(:,:,i);
+    %                 variances = var(projectedTrial,0,1);
+    %                 instances(i,:) = log(variances)';
+    %             end
+    % %             instanceSet = eegtoolkit.util.InstanceSet(instances,labels);
+    %         end
+    %end
+end
+
diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.dot b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.dot
new file mode 100644
index 0000000..de486f9
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.dot
@@ -0,0 +1,6 @@
+/* Created by mdot for Matlab */
+digraph m2html {
+  CSPFilterBankWrapper -> CSPFilterBankWrapper;
+
+  CSPFilterBankWrapper [URL="CSPFilterBankWrapper.html"];
+}
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.html b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.html
new file mode 100644
index 0000000..8be66bf
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.html
@@ -0,0 +1,28 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Dependency Graph for +eegtoolkit/+classification/@CSPFilterBankWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@CSPFilterBankWrapper">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+classification/@CSPFilterBankWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPFilterBankWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@CSPFilterBankWrapper</h1>
+
+<center>
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@CSPFilterBankWrapper" border="2" style="color:#000;">  
+<map name="mainmap">
+<area shape="poly" id="node1" href="CSPFilterBankWrapper.html" title="CSPFilterBankWrapper" alt="" coords="257,29,251,22,233,15,205,10,170,7,131,5,92,7,56,10,28,15,10,22,4,29,10,37,28,43,56,49,92,52,131,53,170,52,205,49,233,43,251,37">
+</map> 
+</center>
+
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.map b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.map
new file mode 100644
index 0000000..daaf177
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/graph.map
@@ -0,0 +1 @@
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diff --git a/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/index.html b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/index.html
new file mode 100644
index 0000000..812d0bc
--- /dev/null
+++ b/doc/+eegtoolkit/+classification/@CSPFilterBankWrapper/index.html
@@ -0,0 +1,32 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Index for Directory +eegtoolkit/+classification/@CSPFilterBankWrapper</title>
+  <meta name="keywords" content="+eegtoolkit/+classification/@CSPFilterBankWrapper">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@CSPFilterBankWrapper">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../../../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPFilterBankWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+
+<h1>Index for +eegtoolkit/+classification/@CSPFilterBankWrapper</h1>
+
+<h2>Matlab files in this directory:</h2>
+<table>
+<tr><td><img src="../../../matlabicon.gif" alt="" border="">&nbsp;<a href="CSPFilterBankWrapper.html">CSPFilterBankWrapper</a></td><td> </td></tr></table>
+
+
+
+<h2>Dependency Graph</h2>
+<ul style="list-style-image:url(../../../simulinkicon.gif)">
+<li>View the <a href="graph.html">Graph</a>.</li>
+</ul>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html
index 951bf5c..155589b 100644
--- a/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/CSPWrapper.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@CSPWrapper</a> &gt; CSPWrapper.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@CSPWrapper</a> &gt; CSPWrapper.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>CSPWrapper
 </h1>
@@ -178,6 +178,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0131     <span class="keyword">end</span>
 0132 <span class="keyword">end</span>
 0133</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html
index 1365d5e..941232d 100644
--- a/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@CSPWrapper">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@CSPWrapper">
+  <title>Dependency Graph for +eegtoolkit/+classification/@CSPWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@CSPWrapper">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+classification/@CSPWrapper">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@CSPWrapper</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@CSPWrapper" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@CSPWrapper" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="CSPWrapper.html" title="CSPWrapper" alt="" coords="158,29,155,22,144,15,127,10,105,7,81,5,57,7,36,10,19,15,8,22,4,29,8,37,19,43,36,49,57,52,81,53,105,52,127,49,144,43,155,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CSPWrapper/index.html b/doc/+eegtoolkit/+classification/@CSPWrapper/index.html
index 5f93366..4cb7dcf 100644
--- a/doc/+eegtoolkit/+classification/@CSPWrapper/index.html
+++ b/doc/+eegtoolkit/+classification/@CSPWrapper/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+classification/@CSPWrapper</title>
-  <meta name="keywords" content="./+eegtoolkit/+classification/@CSPWrapper">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@CSPWrapper">
+  <title>Index for Directory +eegtoolkit/+classification/@CSPWrapper</title>
+  <meta name="keywords" content="+eegtoolkit/+classification/@CSPWrapper">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@CSPWrapper">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CSPWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@CSPWrapper</h1>
+<h1>Index for +eegtoolkit/+classification/@CSPWrapper</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html
index 0a4685a..a7010e7 100644
--- a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@ClassifierBase</a> &gt; ClassifierBase.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@ClassifierBase</a> &gt; ClassifierBase.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ClassifierBase
 </h1>
@@ -28,7 +28,7 @@ <h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src
 
 <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
 <div class="fragment"><pre class="comment"> Abstract class for classification. Implement the functions for any
- classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+ classifier (e.g. LibSVM, LDA, MLR, RFs, Adaboost, etc.)
  
  Properties:
  instanceSet: the training/test set in an InstanceSet structure
@@ -69,7 +69,7 @@ <h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src
 <p><a href="ClassifierBase.m">ClassifierBase.m</a></p>
 <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
 <div class="fragment"><pre>0001 <span class="comment">% Abstract class for classification. Implement the functions for any</span>
-0002 <span class="comment">% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)</span>
+0002 <span class="comment">% classifier (e.g. LibSVM, LDA, MLR, RFs, Adaboost, etc.)</span>
 0003 <span class="comment">%</span>
 0004 <span class="comment">% Properties:</span>
 0005 <span class="comment">% instanceSet: the training/test set in an InstanceSet structure</span>
@@ -110,6 +110,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0040     <span class="keyword">end</span>
 0041     
 0042 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
index ad07e26..531957d 100644
--- a/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/ClassifierBase.m
@@ -1,5 +1,5 @@
 % Abstract class for classification. Implement the functions for any
-% classifier (e.g. LibSVM, LDA, MLR, Decision trees, Adaboost, etc.)
+% classifier (e.g. LibSVM, LDA, MLR, RFs, Adaboost, etc.)
 % 
 % Properties:
 % instanceSet: the training/test set in an InstanceSet structure
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html
index 225726d..408b325 100644
--- a/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@ClassifierBase">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@ClassifierBase">
+  <title>Dependency Graph for +eegtoolkit/+classification/@ClassifierBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@ClassifierBase">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+classification/@ClassifierBase">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@ClassifierBase</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@ClassifierBase" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@ClassifierBase" border="2" style="color:#000;">  
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ClassifierBase/index.html b/doc/+eegtoolkit/+classification/@ClassifierBase/index.html
index bdd3187..70e6013 100644
--- a/doc/+eegtoolkit/+classification/@ClassifierBase/index.html
+++ b/doc/+eegtoolkit/+classification/@ClassifierBase/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+classification/@ClassifierBase</title>
-  <meta name="keywords" content="./+eegtoolkit/+classification/@ClassifierBase">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@ClassifierBase">
+  <title>Index for Directory +eegtoolkit/+classification/@ClassifierBase</title>
+  <meta name="keywords" content="+eegtoolkit/+classification/@ClassifierBase">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@ClassifierBase">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@ClassifierBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@ClassifierBase</h1>
+<h1>Index for +eegtoolkit/+classification/@ClassifierBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html b/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html
index ae526ea..cf87380 100644
--- a/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/CombiCCA.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@CombiCCA</a> &gt; CombiCCA.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@CombiCCA</a> &gt; CombiCCA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>CombiCCA
 </h1>
@@ -218,6 +218,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0171     <span class="keyword">end</span>
 0172 <span class="keyword">end</span>
 0173</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/graph.html b/doc/+eegtoolkit/+classification/@CombiCCA/graph.html
index aa35708..6144892 100644
--- a/doc/+eegtoolkit/+classification/@CombiCCA/graph.html
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
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-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@CombiCCA">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@CombiCCA">
+  <title>Dependency Graph for +eegtoolkit/+classification/@CombiCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@CombiCCA">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+classification/@CombiCCA">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+classification/@CombiCCA</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@CombiCCA</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@CombiCCA" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@CombiCCA" border="2" style="color:#000;">  
 <map name="mainmap">
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@CombiCCA/index.html b/doc/+eegtoolkit/+classification/@CombiCCA/index.html
index 3208d55..d3eef45 100644
--- a/doc/+eegtoolkit/+classification/@CombiCCA/index.html
+++ b/doc/+eegtoolkit/+classification/@CombiCCA/index.html
@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+classification/@CombiCCA</title>
-  <meta name="keywords" content="./+eegtoolkit/+classification/@CombiCCA">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@CombiCCA">
+  <title>Index for Directory +eegtoolkit/+classification/@CombiCCA</title>
+  <meta name="keywords" content="+eegtoolkit/+classification/@CombiCCA">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@CombiCCA">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@CombiCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@CombiCCA</h1>
+<h1>Index for +eegtoolkit/+classification/@CombiCCA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html
index 3bc50b3..553b9e1 100644
--- a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/FusionClassifierWrapper.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@FusionClassifierWrapper</a> &gt; FusionClassifierWrapper.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@FusionClassifierWrapper</a> &gt; FusionClassifierWrapper.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FusionClassifierWrapper
 </h1>
@@ -116,6 +116,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0069     
 0070 <span class="keyword">end</span>
 0071</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html
index 4d5449b..7bfce6d 100644
--- a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html
+++ b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
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-  <title>Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+classification/@FusionClassifierWrapper">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <title>Dependency Graph for +eegtoolkit/+classification/@FusionClassifierWrapper</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+classification/@FusionClassifierWrapper">
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   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,16 +13,16 @@
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+classification/@FusionClassifierWrapper</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@FusionClassifierWrapper" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+classification/@FusionClassifierWrapper" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html b/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html
index 0491c84..316070d 100644
--- a/doc/+eegtoolkit/+classification/@FusionClassifierWrapper/index.html
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@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+classification/@FusionClassifierWrapper</title>
-  <meta name="keywords" content="./+eegtoolkit/+classification/@FusionClassifierWrapper">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <title>Index for Directory +eegtoolkit/+classification/@FusionClassifierWrapper</title>
+  <meta name="keywords" content="+eegtoolkit/+classification/@FusionClassifierWrapper">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@FusionClassifierWrapper">
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@@ -13,9 +13,9 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@FusionClassifierWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@FusionClassifierWrapper</h1>
+<h1>Index for +eegtoolkit/+classification/@FusionClassifierWrapper</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html
index 4d13209..55929cd 100644
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+++ b/doc/+eegtoolkit/+classification/@ITCCA/ITCCA.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@ITCCA</a> &gt; ITCCA.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@ITCCA</a> &gt; ITCCA.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@ITCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@ITCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ITCCA
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diff --git a/doc/+eegtoolkit/+classification/@ITCCA/graph.html b/doc/+eegtoolkit/+classification/@ITCCA/graph.html
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-<h1>Index for ./+eegtoolkit/+classification/@ITCCA</h1>
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 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@L1MCCA</a> &gt; L1MCCA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>L1MCCA
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@L1MCCA/graph.html b/doc/+eegtoolkit/+classification/@L1MCCA/graph.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@L1MCCA</h1>
+<h1>Index for +eegtoolkit/+classification/@L1MCCA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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diff --git a/doc/+eegtoolkit/+classification/@LDA/LDA.html b/doc/+eegtoolkit/+classification/@LDA/LDA.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@LDA</a> &gt; LDA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>LDA
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diff --git a/doc/+eegtoolkit/+classification/@LDA/graph.html b/doc/+eegtoolkit/+classification/@LDA/graph.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@LDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@LDA</h1>
+<h1>Index for +eegtoolkit/+classification/@LDA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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diff --git a/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.html b/doc/+eegtoolkit/+classification/@LIBSVM/LIBSVM.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@LIBSVM</a> &gt; LIBSVM.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@LIBSVM&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@LIBSVM&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>LIBSVM
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-<h1>Index for ./+eegtoolkit/+classification/@LIBSVM</h1>
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 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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-<h1>Index for ./+eegtoolkit/+classification/@LIBSVMFast</h1>
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 <h2>Matlab files in this directory:</h2>
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diff --git a/doc/+eegtoolkit/+classification/@MLDA/MLDA.html b/doc/+eegtoolkit/+classification/@MLDA/MLDA.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@MLDA</a> &gt; MLDA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>MLDA
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diff --git a/doc/+eegtoolkit/+classification/@MLDA/graph.html b/doc/+eegtoolkit/+classification/@MLDA/graph.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLDA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@MLDA</h1>
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 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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diff --git a/doc/+eegtoolkit/+classification/@MLR/MLR.html b/doc/+eegtoolkit/+classification/@MLR/MLR.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@MLR</a> &gt; MLR.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>MLR
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-<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLR</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLR/index.html b/doc/+eegtoolkit/+classification/@MLR/index.html
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+  <meta name="keywords" content="+eegtoolkit/+classification/@MLR">
+  <meta name="description" content="Index for Directory +eegtoolkit/+classification/@MLR">
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@MLR</h1>
+<h1>Index for +eegtoolkit/+classification/@MLR</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.html b/doc/+eegtoolkit/+classification/@MLTREE/MLTREE.html
index 2018789..52ccecd 100644
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@MLTREE</a> &gt; MLTREE.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTREE&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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 <h1>MLTREE
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTREE/graph.html b/doc/+eegtoolkit/+classification/@MLTREE/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLTREE">
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+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+classification/@MLTREE">
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+<h1>Dependency Graph for +eegtoolkit/+classification/@MLTREE</h1>
 
 <center>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTREE/index.html b/doc/+eegtoolkit/+classification/@MLTREE/index.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLTREE&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@MLTREE</h1>
+<h1>Index for +eegtoolkit/+classification/@MLTREE</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html
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+++ b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/MLTboxMulticlass.html
@@ -12,10 +12,10 @@
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MLTboxMulticlass</a> &gt; MLTboxMulticlass.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@MLTboxMulticlass</a> &gt; MLTboxMulticlass.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>MLTboxMulticlass
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MLTboxMulticlass">
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-<h1>Dependency Graph for ./+eegtoolkit/+classification/@MLTboxMulticlass</h1>
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+<h1>Dependency Graph for +eegtoolkit/+classification/@MLTboxMulticlass</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+classification/@MLTboxMulticlass" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MLTboxMulticlass/index.html b/doc/+eegtoolkit/+classification/@MLTboxMulticlass/index.html
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-  <meta name="description" content="Index for Directory ./+eegtoolkit/+classification/@MLTboxMulticlass">
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MLTboxMulticlass&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@MLTboxMulticlass</h1>
+<h1>Index for +eegtoolkit/+classification/@MLTboxMulticlass</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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 <li>View the <a href="graph.html">Graph</a>.</li>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.html b/doc/+eegtoolkit/+classification/@MaxChooser/MaxChooser.html
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 <body>
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="#">@MaxChooser</a> &gt; MaxChooser.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@MaxChooser</a> &gt; MaxChooser.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@MaxChooser&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@MaxChooser&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>MaxChooser
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+classification/@MaxChooser/graph.html b/doc/+eegtoolkit/+classification/@MaxChooser/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+classification/@MaxChooser">
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-<h1>Dependency Graph for ./+eegtoolkit/+classification/@MaxChooser</h1>
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-<h1>Index for ./+eegtoolkit/+classification/@MaxChooser</h1>
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 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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-<h1>Index for ./+eegtoolkit/+classification/@SBLR</h1>
+<h1>Index for +eegtoolkit/+classification/@SBLR</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
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 <li>View the <a href="graph.html">Graph</a>.</li>
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diff --git a/doc/+eegtoolkit/+classification/@SMFA/SMFA.html b/doc/+eegtoolkit/+classification/@SMFA/SMFA.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+classification</a> &gt; <a href="index.html">@SMFA</a> &gt; SMFA.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+classification/@SMFA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+classification/@SMFA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+classification/@SMFA</h1>
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 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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-<h1>Index for ./+eegtoolkit/+experiment/@Experimenter</h1>
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 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+experiment</a> &gt; <a href="index.html">@ResultEvaluator</a> &gt; ResultEvaluator.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+experiment/@ResultEvaluator&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.html b/doc/+eegtoolkit/+experiment/@ResultEvaluator/graph.html
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diff --git a/doc/+eegtoolkit/+experiment/@ResultEvaluator/index.html b/doc/+eegtoolkit/+experiment/@ResultEvaluator/index.html
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-<h1>Index for ./+eegtoolkit/+experiment/@ResultEvaluator</h1>
+<h1>Index for +eegtoolkit/+experiment/@ResultEvaluator</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@CCA/CCA.html b/doc/+eegtoolkit/+featextraction/@CCA/CCA.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@CCA</a> &gt; CCA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@CCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@CCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>CCA
 </h1>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@CCA/graph.html b/doc/+eegtoolkit/+featextraction/@CCA/graph.html
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diff --git a/doc/+eegtoolkit/+featextraction/@CCA/index.html b/doc/+eegtoolkit/+featextraction/@CCA/index.html
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-<h1>Index for ./+eegtoolkit/+featextraction/@CCA</h1>
+<h1>Index for +eegtoolkit/+featextraction/@CCA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@DWT</a> &gt; DWT.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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 <h1>DWT
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diff --git a/doc/+eegtoolkit/+featextraction/@DWT/graph.html b/doc/+eegtoolkit/+featextraction/@DWT/graph.html
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diff --git a/doc/+eegtoolkit/+featextraction/@DWT/index.html b/doc/+eegtoolkit/+featextraction/@DWT/index.html
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+  <title>Index for Directory +eegtoolkit/+featextraction/@DWT</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@DWT">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@DWT">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@DWT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@DWT</h1>
+<h1>Index for +eegtoolkit/+featextraction/@DWT</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html
index 8c3656b..8b43877 100644
--- a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/ERRPFeatures.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@ERRPFeatures</a> &gt; ERRPFeatures.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@ERRPFeatures</a> &gt; ERRPFeatures.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>ERRPFeatures
 </h1>
@@ -81,6 +81,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0034     <span class="keyword">end</span>
 0035     
 0036 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html
index 488795b..8da2cec 100644
--- a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@ERRPFeatures">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@ERRPFeatures</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@ERRPFeatures">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@ERRPFeatures</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@ERRPFeatures" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@ERRPFeatures" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="ERRPFeatures.html" title="ERRPFeatures" alt="" coords="171,29,167,22,155,15,137,10,114,7,88,5,62,7,39,10,21,15,9,22,5,29,9,37,21,43,39,49,62,52,88,53,114,52,137,49,155,43,167,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html
index 5803cba..6e0c501 100644
--- a/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html
+++ b/doc/+eegtoolkit/+featextraction/@ERRPFeatures/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+featextraction/@ERRPFeatures</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@ERRPFeatures">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@ERRPFeatures">
+  <title>Index for Directory +eegtoolkit/+featextraction/@ERRPFeatures</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@ERRPFeatures">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@ERRPFeatures">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@ERRPFeatures&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@ERRPFeatures</h1>
+<h1>Index for +eegtoolkit/+featextraction/@ERRPFeatures</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/FFT.html b/doc/+eegtoolkit/+featextraction/@FFT/FFT.html
index e9f760a..54c5b83 100644
--- a/doc/+eegtoolkit/+featextraction/@FFT/FFT.html
+++ b/doc/+eegtoolkit/+featextraction/@FFT/FFT.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@FFT</a> &gt; FFT.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@FFT</a> &gt; FFT.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FFT
 </h1>
@@ -134,6 +134,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0087    
 0088 <span class="keyword">end</span>
 0089</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/graph.html b/doc/+eegtoolkit/+featextraction/@FFT/graph.html
index c0a8cd9..94af0a7 100644
--- a/doc/+eegtoolkit/+featextraction/@FFT/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@FFT/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@FFT</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@FFT">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@FFT">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@FFT</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@FFT">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@FFT">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@FFT</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@FFT</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@FFT" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@FFT" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="FFT.html" title="FFT" alt="" coords="77,29,76,22,70,15,62,10,52,7,41,5,30,7,20,10,12,15,7,22,5,29,7,37,12,43,20,49,30,52,41,53,52,52,62,49,70,43,76,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FFT/index.html b/doc/+eegtoolkit/+featextraction/@FFT/index.html
index 0e4fd7b..6468ef3 100644
--- a/doc/+eegtoolkit/+featextraction/@FFT/index.html
+++ b/doc/+eegtoolkit/+featextraction/@FFT/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+featextraction/@FFT</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@FFT">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@FFT">
+  <title>Index for Directory +eegtoolkit/+featextraction/@FFT</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@FFT">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@FFT">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@FFT</h1>
+<h1>Index for +eegtoolkit/+featextraction/@FFT</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html
index 1c93476..e201f3c 100644
--- a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@FeatureExtractionBase</a> &gt; FeatureExtractionBase.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@FeatureExtractionBase</a> &gt; FeatureExtractionBase.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FeatureExtractionBase
 </h1>
@@ -28,8 +28,7 @@ <h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src
 
 <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
 <div class="fragment"><pre class="comment"> Abstract class for feature extraction. Implement the functions for any
- preprocessing step (e.g. filtering, artifact removal, sub-sampling,
- rereferencing, etc.
+ feature extractor (e.g. PWelch, FFT, DWT, PYAR, etc.)
  
  Properties:
  instanceSet: Output - the features in an InstanceSet structure
@@ -61,74 +60,73 @@ <h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src
 <p><a href="FeatureExtractionBase.m">FeatureExtractionBase.m</a></p>
 <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../../up.png"></a></h2>
 <div class="fragment"><pre>0001 <span class="comment">% Abstract class for feature extraction. Implement the functions for any</span>
-0002 <span class="comment">% preprocessing step (e.g. filtering, artifact removal, sub-sampling,</span>
-0003 <span class="comment">% rereferencing, etc.</span>
-0004 <span class="comment">%</span>
-0005 <span class="comment">% Properties:</span>
-0006 <span class="comment">% instanceSet: Output - the features in an InstanceSet structure</span>
-0007 <span class="comment">% trials: Input - the signals in a cell of Trial structures</span>
-0008 <span class="comment">%</span>
-0009 <span class="comment">% Functions:</span>
-0010 <span class="comment">%Implement this function to extract the features from the input Trials</span>
-0011 <span class="comment">%and return the features in an instanceSet</span>
-0012 <span class="comment">%   out = obj.extract(in);</span>
-0013 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
-0014 <span class="comment">%is a string with the configuration information and time is of type double.</span>
-0015 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
-0016 <span class="comment">%   time = obj.getTime();</span>
+0002 <span class="comment">% feature extractor (e.g. PWelch, FFT, DWT, PYAR, etc.)</span>
+0003 <span class="comment">%</span>
+0004 <span class="comment">% Properties:</span>
+0005 <span class="comment">% instanceSet: Output - the features in an InstanceSet structure</span>
+0006 <span class="comment">% trials: Input - the signals in a cell of Trial structures</span>
+0007 <span class="comment">%</span>
+0008 <span class="comment">% Functions:</span>
+0009 <span class="comment">%Implement this function to extract the features from the input Trials</span>
+0010 <span class="comment">%and return the features in an instanceSet</span>
+0011 <span class="comment">%   out = obj.extract(in);</span>
+0012 <span class="comment">%Info &amp; run time so that the experiments are easily documented. configInfo</span>
+0013 <span class="comment">%is a string with the configuration information and time is of type double.</span>
+0014 <span class="comment">%   configInfo = obj.getConfigInfo();</span>
+0015 <span class="comment">%   time = obj.getTime();</span>
+0016 
 0017 
-0018 
-0019 classdef (Abstract) <a href="FeatureExtractionBase.html" class="code" title="">FeatureExtractionBase</a> &lt; handle
-0020     <span class="comment">%Base class for a feature transformer</span>
-0021     <span class="comment">%For writing your own FeatureTransformer extend this class and</span>
-0022     <span class="comment">%implement the 'transform' function</span>
-0023     properties (Access = public)
-0024         instanceSet; <span class="comment">% Output: The dataset</span>
-0025         trials;<span class="comment">% Input: The trial signals</span>
-0026         filter;
-0027     <span class="keyword">end</span>
-0028     
-0029     methods (Abstract = true)
-0030         obj = extract(obj);
-0031         configInfo = getConfigInfo(obj);
-0032         time = getTime(obj);
-0033     <span class="keyword">end</span>
-0034     
-0035     methods (Access = public)
-0036         <a name="_sub0" href="#_subfunctions" class="code">function instances = getInstances(obj)</a>
-0037             <span class="comment">%Get the instances (no class labels)</span>
-0038             instances = obj.instanceSet.getInstances;
-0039         <span class="keyword">end</span>
-0040         <a name="_sub1" href="#_subfunctions" class="code">function labels = getLabels(obj)</a>
-0041             <span class="comment">%Get the labels</span>
-0042             labels = obj.instanceSet.getLabels;
-0043         <span class="keyword">end</span>
-0044         
-0045         <a name="_sub2" href="#_subfunctions" class="code">function dataset = getDataset(obj)</a>
-0046             <span class="comment">% same with getInstances but includes the labels as the last</span>
-0047             <span class="comment">% row</span>
-0048             dataset = obj.instanceSet.getDataset;
-0049         <span class="keyword">end</span>
-0050         
-0051         <a name="_sub3" href="#_subfunctions" class="code">function instanceSet = getInstanceSet(obj)</a>
-0052             <span class="comment">% Get the dataset as an 'InstanceSet' class object</span>
-0053             instanceSet = obj.instanceSet;
-0054         <span class="keyword">end</span>
-0055         <a name="_sub4" href="#_subfunctions" class="code">function writeCSV(obj, csvname)</a>
-0056             <span class="comment">% write the dataset to a csv file</span>
-0057             <span class="comment">% Example:</span>
-0058             <span class="comment">%   obj.writeCSV('data.csv');</span>
-0059             obj.instanceSet.writeCSV(csvname);
-0060         <span class="keyword">end</span>
-0061         <a name="_sub5" href="#_subfunctions" class="code">function writeArff(obj, fname)</a>
-0062             <span class="comment">% write the dataset to a weka-readable file (arff)</span>
-0063             <span class="comment">% Caution: filename without extension</span>
-0064             <span class="comment">% Example:</span>
-0065             <span class="comment">%   obj.writeArff('data')</span>
-0066             obj.instanceSet.writeArff(fname);
-0067         <span class="keyword">end</span>
-0068     <span class="keyword">end</span>
-0069 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+0018 classdef (Abstract) <a href="FeatureExtractionBase.html" class="code" title="">FeatureExtractionBase</a> &lt; handle
+0019     <span class="comment">%Base class for a feature transformer</span>
+0020     <span class="comment">%For writing your own FeatureTransformer extend this class and</span>
+0021     <span class="comment">%implement the 'transform' function</span>
+0022     properties (Access = public)
+0023         instanceSet; <span class="comment">% Output: The dataset</span>
+0024         trials;<span class="comment">% Input: The trial signals</span>
+0025         filter;
+0026     <span class="keyword">end</span>
+0027     
+0028     methods (Abstract = true)
+0029         obj = extract(obj);
+0030         configInfo = getConfigInfo(obj);
+0031         time = getTime(obj);
+0032     <span class="keyword">end</span>
+0033     
+0034     methods (Access = public)
+0035         <a name="_sub0" href="#_subfunctions" class="code">function instances = getInstances(obj)</a>
+0036             <span class="comment">%Get the instances (no class labels)</span>
+0037             instances = obj.instanceSet.getInstances;
+0038         <span class="keyword">end</span>
+0039         <a name="_sub1" href="#_subfunctions" class="code">function labels = getLabels(obj)</a>
+0040             <span class="comment">%Get the labels</span>
+0041             labels = obj.instanceSet.getLabels;
+0042         <span class="keyword">end</span>
+0043         
+0044         <a name="_sub2" href="#_subfunctions" class="code">function dataset = getDataset(obj)</a>
+0045             <span class="comment">% same with getInstances but includes the labels as the last</span>
+0046             <span class="comment">% row</span>
+0047             dataset = obj.instanceSet.getDataset;
+0048         <span class="keyword">end</span>
+0049         
+0050         <a name="_sub3" href="#_subfunctions" class="code">function instanceSet = getInstanceSet(obj)</a>
+0051             <span class="comment">% Get the dataset as an 'InstanceSet' class object</span>
+0052             instanceSet = obj.instanceSet;
+0053         <span class="keyword">end</span>
+0054         <a name="_sub4" href="#_subfunctions" class="code">function writeCSV(obj, csvname)</a>
+0055             <span class="comment">% write the dataset to a csv file</span>
+0056             <span class="comment">% Example:</span>
+0057             <span class="comment">%   obj.writeCSV('data.csv');</span>
+0058             obj.instanceSet.writeCSV(csvname);
+0059         <span class="keyword">end</span>
+0060         <a name="_sub5" href="#_subfunctions" class="code">function writeArff(obj, fname)</a>
+0061             <span class="comment">% write the dataset to a weka-readable file (arff)</span>
+0062             <span class="comment">% Caution: filename without extension</span>
+0063             <span class="comment">% Example:</span>
+0064             <span class="comment">%   obj.writeArff('data')</span>
+0065             obj.instanceSet.writeArff(fname);
+0066         <span class="keyword">end</span>
+0067     <span class="keyword">end</span>
+0068 <span class="keyword">end</span></pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
index 29ef454..647966b 100644
--- a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/FeatureExtractionBase.m
@@ -1,6 +1,5 @@
 % Abstract class for feature extraction. Implement the functions for any
-% preprocessing step (e.g. filtering, artifact removal, sub-sampling,
-% rereferencing, etc.
+% feature extractor (e.g. PWelch, FFT, DWT, PYAR, etc.)
 % 
 % Properties:
 % instanceSet: Output - the features in an InstanceSet structure
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html
index 10916ea..da06c80 100644
--- a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@FeatureExtractionBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@FeatureExtractionBase">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@FeatureExtractionBase" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@FeatureExtractionBase" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="FeatureExtractionBase.html" title="FeatureExtractionBase" alt="" coords="247,29,241,22,223,15,197,10,163,7,125,5,88,7,54,10,27,15,10,22,4,29,10,37,27,43,54,49,88,52,125,53,163,52,197,49,223,43,241,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html
index 1cefc39..58a591b 100644
--- a/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html
+++ b/doc/+eegtoolkit/+featextraction/@FeatureExtractionBase/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+featextraction/@FeatureExtractionBase</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@FeatureExtractionBase">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <title>Index for Directory +eegtoolkit/+featextraction/@FeatureExtractionBase</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@FeatureExtractionBase">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@FeatureExtractionBase">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@FeatureExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
+<h1>Index for +eegtoolkit/+featextraction/@FeatureExtractionBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html b/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html
index a39e790..7fd3955 100644
--- a/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/Goertzel.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@Goertzel</a> &gt; Goertzel.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@Goertzel</a> &gt; Goertzel.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Goertzel
 </h1>
@@ -145,6 +145,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0098    
 0099 <span class="keyword">end</span>
 0100</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html
index 04a3c86..d9b8e05 100644
--- a/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@Goertzel">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@Goertzel">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@Goertzel</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@Goertzel">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@Goertzel">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@Goertzel</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@Goertzel" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@Goertzel" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="Goertzel.html" title="Goertzel" alt="" coords="113,29,111,22,103,15,91,10,76,7,59,5,42,7,27,10,14,15,7,22,4,29,7,37,14,43,27,49,42,52,59,53,76,52,91,49,103,43,111,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@Goertzel/index.html b/doc/+eegtoolkit/+featextraction/@Goertzel/index.html
index a9985e3..44af831 100644
--- a/doc/+eegtoolkit/+featextraction/@Goertzel/index.html
+++ b/doc/+eegtoolkit/+featextraction/@Goertzel/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+featextraction/@Goertzel</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@Goertzel">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@Goertzel">
+  <title>Index for Directory +eegtoolkit/+featextraction/@Goertzel</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@Goertzel">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@Goertzel">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@Goertzel&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@Goertzel</h1>
+<h1>Index for +eegtoolkit/+featextraction/@Goertzel</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html
index a32cc8c..658af42 100644
--- a/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/L1MCCA.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@L1MCCA</a> &gt; L1MCCA.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@L1MCCA</a> &gt; L1MCCA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>L1MCCA
 </h1>
@@ -72,6 +72,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0025         <span class="keyword">end</span>
 0026     <span class="keyword">end</span>
 0027 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html
index f1e9037..e98399a 100644
--- a/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@L1MCCA">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@L1MCCA">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@L1MCCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@L1MCCA">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@L1MCCA">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@L1MCCA</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@L1MCCA" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@L1MCCA" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="L1MCCA.html" title="L1MCCA" alt="" coords="129,29,126,22,117,15,103,10,86,7,67,5,47,7,30,10,16,15,7,22,4,29,7,37,16,43,30,49,47,52,67,53,86,52,103,49,117,43,126,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html b/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html
index 73d7594..5812eb8 100644
--- a/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html
+++ b/doc/+eegtoolkit/+featextraction/@L1MCCA/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
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-  <title>Index for Directory ./+eegtoolkit/+featextraction/@L1MCCA</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@L1MCCA">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@L1MCCA">
+  <title>Index for Directory +eegtoolkit/+featextraction/@L1MCCA</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@L1MCCA">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@L1MCCA">
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   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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 <body>
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@L1MCCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@L1MCCA</h1>
+<h1>Index for +eegtoolkit/+featextraction/@L1MCCA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html
index ad43195..045785d 100644
--- a/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/MLR_Transf.html
@@ -12,10 +12,10 @@
 </head>
 <body>
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@MLR_Transf</a> &gt; MLR_Transf.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@MLR_Transf</a> &gt; MLR_Transf.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>MLR_Transf
 </h1>
@@ -109,6 +109,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0062     
 0063 <span class="keyword">end</span>
 0064</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html
index 12815ea..e6a0e5e 100644
--- a/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/graph.html
@@ -2,9 +2,9 @@
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-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@MLR_Transf">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@MLR_Transf">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@MLR_Transf</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@MLR_Transf">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@MLR_Transf">
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@MLR_Transf</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@MLR_Transf" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@MLR_Transf" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html b/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html
index 64166c1..5160b57 100644
--- a/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html
+++ b/doc/+eegtoolkit/+featextraction/@MLR_Transf/index.html
@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+featextraction/@MLR_Transf</title>
-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@MLR_Transf">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@MLR_Transf">
+  <title>Index for Directory +eegtoolkit/+featextraction/@MLR_Transf</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@MLR_Transf">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@MLR_Transf">
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@MLR_Transf&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@MLR_Transf</h1>
+<h1>Index for +eegtoolkit/+featextraction/@MLR_Transf</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html
index 88fe395..431deaa 100644
--- a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/PSDExtractionBase.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PSDExtractionBase</a> &gt; PSDExtractionBase.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@PSDExtractionBase</a> &gt; PSDExtractionBase.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PSDExtractionBase
 </h1>
@@ -50,6 +50,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0005         pff; <span class="comment">% The frequencies of the spectrum</span>
 0006     <span class="keyword">end</span>
 0007 <span class="keyword">end</span></pre></div>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html
index 6467381..75ab7a3 100644
--- a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html
+++ b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/graph.html
@@ -2,9 +2,9 @@
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-  <title>Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featextraction/@PSDExtractionBase">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@PSDExtractionBase</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@PSDExtractionBase">
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@@ -13,16 +13,16 @@
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@PSDExtractionBase</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PSDExtractionBase" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@PSDExtractionBase" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/index.html b/doc/+eegtoolkit/+featextraction/@PSDExtractionBase/index.html
index bdf93e0..1a77a17 100644
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-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PSDExtractionBase">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <title>Index for Directory +eegtoolkit/+featextraction/@PSDExtractionBase</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@PSDExtractionBase">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@PSDExtractionBase">
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@@ -13,9 +13,9 @@
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PSDExtractionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@PSDExtractionBase</h1>
+<h1>Index for +eegtoolkit/+featextraction/@PSDExtractionBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html
index 07f77f4..fe70e42 100644
--- a/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html
+++ b/doc/+eegtoolkit/+featextraction/@PWelch/PWelch.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PWelch</a> &gt; PWelch.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@PWelch</a> &gt; PWelch.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PWelch
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@@ -162,6 +162,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0115    
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/graph.html b/doc/+eegtoolkit/+featextraction/@PWelch/graph.html
index 9d3d176..8903edf 100644
--- a/doc/+eegtoolkit/+featextraction/@PWelch/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PWelch">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@PWelch</title>
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+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@PWelch">
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelch</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@PWelch</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PWelch" border="2" style="color:#000;">  
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelch/index.html b/doc/+eegtoolkit/+featextraction/@PWelch/index.html
index e8b3357..a97ad01 100644
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-  <meta name="keywords" content="./+eegtoolkit/+featextraction/@PWelch">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PWelch">
+  <title>Index for Directory +eegtoolkit/+featextraction/@PWelch</title>
+  <meta name="keywords" content="+eegtoolkit/+featextraction/@PWelch">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featextraction/@PWelch">
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelch&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@PWelch</h1>
+<h1>Index for +eegtoolkit/+featextraction/@PWelch</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html
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--- a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html
+++ b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/PWelchExperimental.html
@@ -12,10 +12,10 @@
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 <body>
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PWelchExperimental</a> &gt; PWelchExperimental.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@PWelchExperimental</a> &gt; PWelchExperimental.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PWelchExperimental
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@@ -178,6 +178,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html
index 2dff583..4a34537 100644
--- a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PWelchExperimental">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@PWelchExperimental</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featextraction/@PWelchExperimental">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@PWelchExperimental">
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PWelchExperimental</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@PWelchExperimental</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PWelchExperimental" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@PWelchExperimental" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featextraction/@PWelchExperimental/index.html b/doc/+eegtoolkit/+featextraction/@PWelchExperimental/index.html
index ace320f..7365ef0 100644
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-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featextraction/@PWelchExperimental">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PWelchExperimental&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@PWelchExperimental</h1>
+<h1>Index for +eegtoolkit/+featextraction/@PWelchExperimental</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html
index 48d8c20..67c2444 100644
--- a/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html
+++ b/doc/+eegtoolkit/+featextraction/@PYAR/PYAR.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@PYAR</a> &gt; PYAR.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@PYAR</a> &gt; PYAR.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PYAR
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@@ -142,6 +142,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0095    
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/graph.html b/doc/+eegtoolkit/+featextraction/@PYAR/graph.html
index 205339d..677f3e1 100644
--- a/doc/+eegtoolkit/+featextraction/@PYAR/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@PYAR">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@PYAR</title>
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+  <meta name="description" content="Dependency graph for +eegtoolkit/+featextraction/@PYAR">
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@@ -13,16 +13,16 @@
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@PYAR</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@PYAR</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@PYAR" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featextraction/@PYAR" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@PYAR/index.html b/doc/+eegtoolkit/+featextraction/@PYAR/index.html
index b95fd23..7e25ef9 100644
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@PYAR&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@PYAR</h1>
+<h1>Index for +eegtoolkit/+featextraction/@PYAR</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html
index 873d3ac..1765d5c 100644
--- a/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html
+++ b/doc/+eegtoolkit/+featextraction/@RawSignal/RawSignal.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="#">@RawSignal</a> &gt; RawSignal.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@RawSignal</a> &gt; RawSignal.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>RawSignal
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html b/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html
index 14a5ac5..09ca980 100644
--- a/doc/+eegtoolkit/+featextraction/@RawSignal/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featextraction/@RawSignal">
+  <title>Dependency Graph for +eegtoolkit/+featextraction/@RawSignal</title>
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-<h1>Dependency Graph for ./+eegtoolkit/+featextraction/@RawSignal</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featextraction/@RawSignal</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@RawSignal" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@RawSignal/index.html b/doc/+eegtoolkit/+featextraction/@RawSignal/index.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@RawSignal&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@RawSignal</h1>
+<h1>Index for +eegtoolkit/+featextraction/@RawSignal</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/STFT.html b/doc/+eegtoolkit/+featextraction/@STFT/STFT.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featextraction</a> &gt; <a href="index.html">@STFT</a> &gt; STFT.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>STFT
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featextraction/@STFT/graph.html b/doc/+eegtoolkit/+featextraction/@STFT/graph.html
index 97c3e7e..cf0f187 100644
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 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featextraction/@STFT" border="2" style="color:#000;">  
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diff --git a/doc/+eegtoolkit/+featextraction/@STFT/index.html b/doc/+eegtoolkit/+featextraction/@STFT/index.html
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+featextraction/@STFT&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featextraction/@STFT</h1>
+<h1>Index for +eegtoolkit/+featextraction/@STFT</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/FEAST.html b/doc/+eegtoolkit/+featselection/@FEAST/FEAST.html
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@@ -12,10 +12,10 @@
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="index.html">@FEAST</a> &gt; FEAST.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FEAST
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FEAST/graph.html b/doc/+eegtoolkit/+featselection/@FEAST/graph.html
index 079ad91..a9ba5bc 100644
--- a/doc/+eegtoolkit/+featselection/@FEAST/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@FEAST">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@FEAST">
+  <title>Dependency Graph for +eegtoolkit/+featselection/@FEAST</title>
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-<h1>Dependency Graph for ./+eegtoolkit/+featselection/@FEAST</h1>
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 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@FEAST" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featselection/@FEAST/index.html b/doc/+eegtoolkit/+featselection/@FEAST/index.html
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+  <title>Index for Directory +eegtoolkit/+featselection/@FEAST</title>
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@FEAST&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featselection/@FEAST</h1>
+<h1>Index for +eegtoolkit/+featselection/@FEAST</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/FeatureSelectionBase.html
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 <body>
 <a name="_top"></a>
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="index.html">@FeatureSelectionBase</a> &gt; FeatureSelectionBase.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/graph.html
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/index.html b/doc/+eegtoolkit/+featselection/@FeatureSelectionBase/index.html
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@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@FeatureSelectionBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featselection/@FeatureSelectionBase</h1>
+<h1>Index for +eegtoolkit/+featselection/@FeatureSelectionBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/PCA.html b/doc/+eegtoolkit/+featselection/@PCA/PCA.html
index 41fbbc6..935a7c4 100644
--- a/doc/+eegtoolkit/+featselection/@PCA/PCA.html
+++ b/doc/+eegtoolkit/+featselection/@PCA/PCA.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@PCA</a> &gt; PCA.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="index.html">@PCA</a> &gt; PCA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PCA
 </h1>
@@ -77,6 +77,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0030         <span class="keyword">end</span>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/graph.html b/doc/+eegtoolkit/+featselection/@PCA/graph.html
index 905c0d7..4bfeb29 100644
--- a/doc/+eegtoolkit/+featselection/@PCA/graph.html
+++ b/doc/+eegtoolkit/+featselection/@PCA/graph.html
@@ -2,9 +2,9 @@
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 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featselection/@PCA</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@PCA">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@PCA">
+  <title>Dependency Graph for +eegtoolkit/+featselection/@PCA</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featselection/@PCA">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featselection/@PCA">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,16 +13,16 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featselection/@PCA</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featselection/@PCA</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@PCA" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featselection/@PCA" border="2" style="color:#000;">  
 <map name="mainmap">
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@PCA/index.html b/doc/+eegtoolkit/+featselection/@PCA/index.html
index ddb326c..3d2e250 100644
--- a/doc/+eegtoolkit/+featselection/@PCA/index.html
+++ b/doc/+eegtoolkit/+featselection/@PCA/index.html
@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+featselection/@PCA</title>
-  <meta name="keywords" content="./+eegtoolkit/+featselection/@PCA">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@PCA">
+  <title>Index for Directory +eegtoolkit/+featselection/@PCA</title>
+  <meta name="keywords" content="+eegtoolkit/+featselection/@PCA">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featselection/@PCA">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,9 +13,9 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@PCA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featselection/@PCA</h1>
+<h1>Index for +eegtoolkit/+featselection/@PCA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/SVD.html b/doc/+eegtoolkit/+featselection/@SVD/SVD.html
index 61e1deb..01f8d50 100644
--- a/doc/+eegtoolkit/+featselection/@SVD/SVD.html
+++ b/doc/+eegtoolkit/+featselection/@SVD/SVD.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="#">@SVD</a> &gt; SVD.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+featselection</a> &gt; <a href="index.html">@SVD</a> &gt; SVD.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>SVD
 </h1>
@@ -77,6 +77,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0030         <span class="keyword">end</span>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/graph.html b/doc/+eegtoolkit/+featselection/@SVD/graph.html
index c601b51..a664cb6 100644
--- a/doc/+eegtoolkit/+featselection/@SVD/graph.html
+++ b/doc/+eegtoolkit/+featselection/@SVD/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+featselection/@SVD</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+featselection/@SVD">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+featselection/@SVD">
+  <title>Dependency Graph for +eegtoolkit/+featselection/@SVD</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+featselection/@SVD">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+featselection/@SVD">
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@@ -13,16 +13,16 @@
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+featselection/@SVD</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+featselection/@SVD</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+featselection/@SVD" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+featselection/@SVD" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+featselection/@SVD/index.html b/doc/+eegtoolkit/+featselection/@SVD/index.html
index 865923a..9fa740d 100644
--- a/doc/+eegtoolkit/+featselection/@SVD/index.html
+++ b/doc/+eegtoolkit/+featselection/@SVD/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
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 <head>
-  <title>Index for Directory ./+eegtoolkit/+featselection/@SVD</title>
-  <meta name="keywords" content="./+eegtoolkit/+featselection/@SVD">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+featselection/@SVD">
+  <title>Index for Directory +eegtoolkit/+featselection/@SVD</title>
+  <meta name="keywords" content="+eegtoolkit/+featselection/@SVD">
+  <meta name="description" content="Index for Directory +eegtoolkit/+featselection/@SVD">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,9 +13,9 @@
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 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+featselection/@SVD&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+featselection/@SVD</h1>
+<h1>Index for +eegtoolkit/+featselection/@SVD</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html
index 6491268..c2b9df7 100644
--- a/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html
+++ b/doc/+eegtoolkit/+preprocessing/@Amuse/Amuse.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Amuse</a> &gt; Amuse.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@Amuse</a> &gt; Amuse.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Amuse
 </h1>
@@ -147,6 +147,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html b/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html
index 48d9378..a293083 100644
--- a/doc/+eegtoolkit/+preprocessing/@Amuse/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+preprocessing/@Amuse">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Amuse">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@Amuse</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+preprocessing/@Amuse">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+preprocessing/@Amuse">
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   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,16 +13,16 @@
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 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Amuse</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@Amuse</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Amuse" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+preprocessing/@Amuse" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Amuse/index.html b/doc/+eegtoolkit/+preprocessing/@Amuse/index.html
index b5a54a5..0525777 100644
--- a/doc/+eegtoolkit/+preprocessing/@Amuse/index.html
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@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+preprocessing/@Amuse</title>
-  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@Amuse">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Amuse">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@Amuse</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@Amuse">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@Amuse">
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   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
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@@ -13,9 +13,9 @@
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 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Amuse&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@Amuse</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@Amuse</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html
index 76b4074..9c51504 100644
--- a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html
+++ b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/DigitalFilter.html
@@ -12,10 +12,10 @@
 </head>
 <body>
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-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@DigitalFilter</a> &gt; DigitalFilter.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@DigitalFilter</a> &gt; DigitalFilter.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>DigitalFilter
 </h1>
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html
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--- a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@DigitalFilter</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+preprocessing/@DigitalFilter">
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-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@DigitalFilter</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@DigitalFilter</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@DigitalFilter" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+preprocessing/@DigitalFilter/index.html b/doc/+eegtoolkit/+preprocessing/@DigitalFilter/index.html
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-  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@DigitalFilter">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@DigitalFilter">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@DigitalFilter</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@DigitalFilter">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@DigitalFilter">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@DigitalFilter&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@DigitalFilter</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@DigitalFilter</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html
index 90734ba..5df07ea 100644
--- a/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html
+++ b/doc/+eegtoolkit/+preprocessing/@FastICA/FastICA.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@FastICA</a> &gt; FastICA.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@FastICA</a> &gt; FastICA.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FastICA
 </h1>
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 0045     
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html b/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html
index a8abb55..a34a2c0 100644
--- a/doc/+eegtoolkit/+preprocessing/@FastICA/graph.html
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@FastICA">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@FastICA</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+preprocessing/@FastICA">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+preprocessing/@FastICA">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@FastICA</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@FastICA</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@FastICA" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+preprocessing/@FastICA" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+preprocessing/@FastICA/index.html b/doc/+eegtoolkit/+preprocessing/@FastICA/index.html
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@@ -2,9 +2,9 @@
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-  <title>Index for Directory ./+eegtoolkit/+preprocessing/@FastICA</title>
-  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@FastICA">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@FastICA">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@FastICA</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@FastICA">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@FastICA">
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@@ -13,9 +13,9 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@FastICA&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@FastICA</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@FastICA</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html
index 87198d7..fee69e9 100644
--- a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html
+++ b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/PreprocessingBase.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@PreprocessingBase</a> &gt; PreprocessingBase.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@PreprocessingBase</a> &gt; PreprocessingBase.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>PreprocessingBase
 </h1>
@@ -90,6 +90,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0030     
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@PreprocessingBase</title>
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@PreprocessingBase</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@PreprocessingBase" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+preprocessing/@PreprocessingBase" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/index.html b/doc/+eegtoolkit/+preprocessing/@PreprocessingBase/index.html
index a2d767b..b099f28 100644
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-  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@PreprocessingBase">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@PreprocessingBase</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@PreprocessingBase">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@PreprocessingBase">
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 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@PreprocessingBase&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@PreprocessingBase</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@PreprocessingBase</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/Rereferencing.html
index 26c098e..aa30f89 100644
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@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Rereferencing</a> &gt; Rereferencing.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@Rereferencing</a> &gt; Rereferencing.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Rereferencing
 </h1>
@@ -90,6 +90,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0043     
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Rereferencing">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@Rereferencing</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+preprocessing/@Rereferencing">
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-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Rereferencing</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@Rereferencing</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Rereferencing" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+preprocessing/@Rereferencing/index.html b/doc/+eegtoolkit/+preprocessing/@Rereferencing/index.html
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Rereferencing">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@Rereferencing</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@Rereferencing">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@Rereferencing">
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Rereferencing&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@Rereferencing</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@Rereferencing</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html
index 3b1cfb2..cbe204b 100644
--- a/doc/+eegtoolkit/+preprocessing/@SampleSelection/SampleSelection.html
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@@ -12,10 +12,10 @@
 </head>
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 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@SampleSelection</a> &gt; SampleSelection.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@SampleSelection</a> &gt; SampleSelection.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>SampleSelection
 </h1>
@@ -138,6 +138,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/graph.html
index 6bad530..1e2df1a 100644
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@@ -2,9 +2,9 @@
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@SampleSelection">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@SampleSelection</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+preprocessing/@SampleSelection">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+preprocessing/@SampleSelection">
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@SampleSelection</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@SampleSelection</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@SampleSelection" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/+eegtoolkit/+preprocessing/@SampleSelection/index.html b/doc/+eegtoolkit/+preprocessing/@SampleSelection/index.html
index 95496df..4b6ebc0 100644
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-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@SampleSelection">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@SampleSelection</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@SampleSelection">
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@SampleSelection&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@SampleSelection</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@SampleSelection</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/Windsorize.html
index 33241d4..8a6667b 100644
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@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="#">@Windsorize</a> &gt; Windsorize.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+preprocessing</a> &gt; <a href="index.html">@Windsorize</a> &gt; Windsorize.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Windsorize
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@@ -109,6 +109,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0062     
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/graph.html
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-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+preprocessing/@Windsorize">
+  <title>Dependency Graph for +eegtoolkit/+preprocessing/@Windsorize</title>
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@@ -13,16 +13,16 @@
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 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+preprocessing/@Windsorize</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+preprocessing/@Windsorize</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+preprocessing/@Windsorize" border="2" style="color:#000;">  
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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\ No newline at end of file
diff --git a/doc/+eegtoolkit/+preprocessing/@Windsorize/index.html b/doc/+eegtoolkit/+preprocessing/@Windsorize/index.html
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-  <meta name="keywords" content="./+eegtoolkit/+preprocessing/@Windsorize">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+preprocessing/@Windsorize">
+  <title>Index for Directory +eegtoolkit/+preprocessing/@Windsorize</title>
+  <meta name="keywords" content="+eegtoolkit/+preprocessing/@Windsorize">
+  <meta name="description" content="Index for Directory +eegtoolkit/+preprocessing/@Windsorize">
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 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+preprocessing/@Windsorize&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+preprocessing/@Windsorize</h1>
+<h1>Index for +eegtoolkit/+preprocessing/@Windsorize</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.html b/doc/+eegtoolkit/+util/@FusionInstanceSet/FusionInstanceSet.html
index 777c40c..062ee71 100644
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@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@FusionInstanceSet</a> &gt; FusionInstanceSet.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="index.html">@FusionInstanceSet</a> &gt; FusionInstanceSet.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@FusionInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@FusionInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>FusionInstanceSet
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-<h1>Index for ./+eegtoolkit/+util/@FusionInstanceSet</h1>
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 <table>
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-<h1>Index for ./+eegtoolkit/+util/@InstanceSet</h1>
+<h1>Index for +eegtoolkit/+util/@InstanceSet</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="index.html">@L1MCCAInstanceSet</a> &gt; L1MCCAInstanceSet.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@L1MCCAInstanceSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
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+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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-<h1>Index for ./+eegtoolkit/+util/@L1MCCAInstanceSet</h1>
+<h1>Index for +eegtoolkit/+util/@L1MCCAInstanceSet</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
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diff --git a/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.html b/doc/+eegtoolkit/+util/@LSLWrapper/LSLWrapper.html
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="index.html">@LSLWrapper</a> &gt; LSLWrapper.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@LSLWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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-<h1>Dependency Graph for ./+eegtoolkit/+util/@LSLWrapper</h1>
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+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@LSLWrapper&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+util/@LSLWrapper</h1>
+<h1>Index for +eegtoolkit/+util/@LSLWrapper</h1>
 
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 <table>
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@RawSignalSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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-<h1>Index for ./+eegtoolkit/+util/@RawSignalSet</h1>
+<h1>Index for +eegtoolkit/+util/@RawSignalSet</h1>
 
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+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="index.html">@ResultSet</a> &gt; ResultSet.m</div>
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@ResultSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@ResultSet&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
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-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
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+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+util/@Session" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="Session.html" title="Session" alt="" coords="105,29,102,22,95,15,84,10,70,7,55,5,39,7,25,10,14,15,7,22,4,29,7,37,14,43,25,49,39,52,55,53,70,52,84,49,95,43,102,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Session/index.html b/doc/+eegtoolkit/+util/@Session/index.html
index 6608428..91d17af 100644
--- a/doc/+eegtoolkit/+util/@Session/index.html
+++ b/doc/+eegtoolkit/+util/@Session/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+util/@Session</title>
-  <meta name="keywords" content="./+eegtoolkit/+util/@Session">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@Session">
+  <title>Index for Directory +eegtoolkit/+util/@Session</title>
+  <meta name="keywords" content="+eegtoolkit/+util/@Session">
+  <meta name="description" content="Index for Directory +eegtoolkit/+util/@Session">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@Session&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+util/@Session</h1>
+<h1>Index for +eegtoolkit/+util/@Session</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/Trial.html b/doc/+eegtoolkit/+util/@Trial/Trial.html
index 5c35357..e9b86a0 100644
--- a/doc/+eegtoolkit/+util/@Trial/Trial.html
+++ b/doc/+eegtoolkit/+util/@Trial/Trial.html
@@ -12,10 +12,10 @@
 </head>
 <body>
 <a name="_top"></a>
-<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="#">@Trial</a> &gt; Trial.m</div>
+<div><a href="../../../index.html">Home</a> &gt;  <a href="#">+eegtoolkit</a> &gt; <a href="#">+util</a> &gt; <a href="index.html">@Trial</a> &gt; Trial.m</div>
 
 <!--<table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>-->
 
 <h1>Trial
 </h1>
@@ -110,6 +110,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0050     
 0051 <span class="keyword">end</span>
 0052</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/graph.html b/doc/+eegtoolkit/+util/@Trial/graph.html
index 150af9a..2dba938 100644
--- a/doc/+eegtoolkit/+util/@Trial/graph.html
+++ b/doc/+eegtoolkit/+util/@Trial/graph.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Dependency Graph for ./+eegtoolkit/+util/@Trial</title>
-  <meta name="keywords" content="dependency, graph, dependence, ./+eegtoolkit/+util/@Trial">
-  <meta name="description" content="Dependency graph for ./+eegtoolkit/+util/@Trial">
+  <title>Dependency Graph for +eegtoolkit/+util/@Trial</title>
+  <meta name="keywords" content="dependency, graph, dependence, +eegtoolkit/+util/@Trial">
+  <meta name="description" content="Dependency graph for +eegtoolkit/+util/@Trial">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,16 +13,16 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
-<h1>Dependency Graph for ./+eegtoolkit/+util/@Trial</h1>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<h1>Dependency Graph for +eegtoolkit/+util/@Trial</h1>
 
 <center>
-<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for ./+eegtoolkit/+util/@Trial" border="2" style="color:#000;">  
+<img src="graph.png" usemap="#mainmap" alt="Dependency Graph for +eegtoolkit/+util/@Trial" border="2" style="color:#000;">  
 <map name="mainmap">
 <area shape="poly" id="node1" href="Trial.html" title="Trial" alt="" coords="79,29,77,22,71,15,63,10,53,7,41,5,30,7,19,10,11,15,6,22,4,29,6,37,11,43,19,49,30,52,41,53,53,52,63,49,71,43,77,37">
 </map> 
 </center>
 
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/+eegtoolkit/+util/@Trial/index.html b/doc/+eegtoolkit/+util/@Trial/index.html
index 0894d44..61fb45f 100644
--- a/doc/+eegtoolkit/+util/@Trial/index.html
+++ b/doc/+eegtoolkit/+util/@Trial/index.html
@@ -2,9 +2,9 @@
                 "http://www.w3.org/TR/REC-html40/loose.dtd">
 <html>
 <head>
-  <title>Index for Directory ./+eegtoolkit/+util/@Trial</title>
-  <meta name="keywords" content="./+eegtoolkit/+util/@Trial">
-  <meta name="description" content="Index for Directory ./+eegtoolkit/+util/@Trial">
+  <title>Index for Directory +eegtoolkit/+util/@Trial</title>
+  <meta name="keywords" content="+eegtoolkit/+util/@Trial">
+  <meta name="description" content="Index for Directory +eegtoolkit/+util/@Trial">
   <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
   <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
   <meta name="robots" content="index, follow">
@@ -13,9 +13,9 @@
 <body>
 <a name="_top"></a>
 <table width="100%"><tr><td align="left"><a href="../../../index.html"><img alt="<" border="0" src="../../../left.png">&nbsp;Master index</a></td>
-<td align="right"><a href="index.html">Index for ./+eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
+<td align="right"><a href="index.html">Index for +eegtoolkit/+util/@Trial&nbsp;<img alt=">" border="0" src="../../../right.png"></a></td></tr></table>
 
-<h1>Index for ./+eegtoolkit/+util/@Trial</h1>
+<h1>Index for +eegtoolkit/+util/@Trial</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
@@ -27,6 +27,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../../../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleCSP.html b/doc/exampleCSP.html
index b25686a..3cb4202 100644
--- a/doc/exampleCSP.html
+++ b/doc/exampleCSP.html
@@ -82,6 +82,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0037 experiment.run(3);
 0038 accuracy = experiment.results{1}.getAccuracy();
 0039</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleCombiCCA.html b/doc/exampleCombiCCA.html
index a939c0d..95ad859 100644
--- a/doc/exampleCombiCCA.html
+++ b/doc/exampleCombiCCA.html
@@ -88,6 +88,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0043         <span class="comment">% accuracy = experiment.results{1}.getAccuracy();</span>
 0044     <span class="keyword">end</span>
 0045 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleDefault.html b/doc/exampleDefault.html
index 46b5f13..e9ffd3e 100644
--- a/doc/exampleDefault.html
+++ b/doc/exampleDefault.html
@@ -92,6 +92,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0043 <span class="comment">%get the configuration used (for reporting)</span>
 0044 experiment.getExperimentInfo
 0045 experiment.getTime</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleEPOCCCASVM.html b/doc/exampleEPOCCCASVM.html
index 45f41a8..bd01d3e 100644
--- a/doc/exampleEPOCCCASVM.html
+++ b/doc/exampleEPOCCCASVM.html
@@ -100,6 +100,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0050 <span class="comment">%get the configuration used (for reporting)</span>
 0051 <span class="comment">% experiment.getExperimentInfo</span>
 0052 <span class="comment">% experiment.getTime</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleERRP.html b/doc/exampleERRP.html
index 80d30c3..c9e3148 100644
--- a/doc/exampleERRP.html
+++ b/doc/exampleERRP.html
@@ -86,6 +86,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0041 
 0042 accuracies'
 0043 fprintf(<span class="string">'mean acc = %.2f\n'</span>,mean(accuracies));</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleERRPSSVEPDemo.html b/doc/exampleERRPSSVEPDemo.html
new file mode 100644
index 0000000..d629350
--- /dev/null
+++ b/doc/exampleERRPSSVEPDemo.html
@@ -0,0 +1,94 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
+                "http://www.w3.org/TR/REC-html40/loose.dtd">
+<html>
+<head>
+  <title>Description of exampleERRPSSVEPDemo</title>
+  <meta name="keywords" content="exampleERRPSSVEPDemo">
+  <meta name="description" content="d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');">
+  <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+  <meta name="generator" content="m2html v1.5 &copy; 2003-2005 Guillaume Flandin">
+  <meta name="robots" content="index, follow">
+  <link type="text/css" rel="stylesheet" href="../m2html.css">
+</head>
+<body>
+<a name="_top"></a>
+<div><a href="../index.html">Home</a> &gt;  <a href="index.html">.</a> &gt; exampleERRPSSVEPDemo.m</div>
+
+<!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png">&nbsp;Master index</a></td>
+<td align="right"><a href="index.html">Index for .&nbsp;<img alt=">" border="0" src="../right.png"></a></td></tr></table>-->
+
+<h1>exampleERRPSSVEPDemo
+</h1>
+
+<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</strong></div>
+
+<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="box"><strong>This is a script file. </strong></div>
+
+<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre class="comment"> d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</pre></div>
+
+<!-- crossreference -->
+<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+This function calls:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+This function is called by:
+<ul style="list-style-image:url(../matlabicon.gif)">
+</ul>
+<!-- crossreference -->
+
+
+<h2><a name="_download"></a>DOWNLOAD <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<p><a href="exampleERRPSSVEPDemo.m">exampleERRPSSVEPDemo.m</a></p>
+<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
+<div class="fragment"><pre>0001 <span class="comment">% d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');</span>
+0002 
+0003 sess = eegtoolkit.util.Session;
+0004 sess.loadSubjectSession(8,5,2);
+0005 
+0006 [z,p,k]=butter(3,[1,10]/64);
+0007 [s,g]=zp2sos(z,p,k);
+0008 Hd = dfilt.df2sos(s,g);
+0009 df = eegtoolkit.preprocessing.DigitalFilter; <span class="comment">%</span>
+0010 df.filt = Hd;
+0011 
+0012 ss = eegtoolkit.preprocessing.SampleSelection;
+0013 ss.channels = [1:14];
+0014 ss.sampleRange = [1:6:200];
+0015 
+0016 extr = {};
+0017 <span class="keyword">for</span> i=1:3
+0018     extr{i} = eegtoolkit.featextraction.PWelch;
+0019     extr{i}.channel = 1;
+0020 <span class="keyword">end</span>
+0021 
+0022 aggr = eegtoolkit.aggregation.ChannelConcat;
+0023 
+0024 classif = eegtoolkit.classification.LIBSVM;
+0025 classif.kernel = classif.KERNEL_RBF;
+0026 classif.gamma = 1/9;
+0027 classif.cost = 1;
+0028 
+0029 <span class="comment">%Setup experiment</span>
+0030 experiment = eegtoolkit.experiment.Experimenter;
+0031 experiment.session = sess;
+0032 experiment.preprocessing = {df,ss};
+0033 experiment.featextraction = extr;
+0034 experiment.aggregator = aggr;
+0035 experiment.classification = classif;
+0036 experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+0037 
+0038 experiment.run(10);
+0039 
+0040 accuracies = [];
+0041 <span class="keyword">for</span> i=1:length(experiment.results)
+0042     accuracies(i) = experiment.results{i}.getAccuracy();
+0043 <span class="keyword">end</span>
+0044 
+0045 accuracies'
+0046 fprintf(<span class="string">'mean acc = %.2f\n'</span>,mean(accuracies));</pre></div>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+</body>
+</html>
\ No newline at end of file
diff --git a/doc/exampleERRPSSVEPDemo.m b/doc/exampleERRPSSVEPDemo.m
new file mode 100644
index 0000000..4bd172f
--- /dev/null
+++ b/doc/exampleERRPSSVEPDemo.m
@@ -0,0 +1,46 @@
+% d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter');
+
+sess = eegtoolkit.util.Session;
+sess.loadSubjectSession(8,5,2);
+
+[z,p,k]=butter(3,[1,10]/64);
+[s,g]=zp2sos(z,p,k);
+Hd = dfilt.df2sos(s,g);
+df = eegtoolkit.preprocessing.DigitalFilter; %
+df.filt = Hd;
+
+ss = eegtoolkit.preprocessing.SampleSelection;
+ss.channels = [1:14];
+ss.sampleRange = [1:6:200];
+
+extr = {};
+for i=1:3
+    extr{i} = eegtoolkit.featextraction.PWelch;
+    extr{i}.channel = 1;
+end
+
+aggr = eegtoolkit.aggregation.ChannelConcat;
+
+classif = eegtoolkit.classification.LIBSVM;
+classif.kernel = classif.KERNEL_RBF;
+classif.gamma = 1/9;
+classif.cost = 1;
+
+%Setup experiment
+experiment = eegtoolkit.experiment.Experimenter;
+experiment.session = sess;
+experiment.preprocessing = {df,ss};
+experiment.featextraction = extr;
+experiment.aggregator = aggr;
+experiment.classification = classif;
+experiment.evalMethod = experiment.EVAL_METHOD_XFOLD_CV;
+
+experiment.run(10);
+
+accuracies = [];
+for i=1:length(experiment.results)
+    accuracies(i) = experiment.results{i}.getAccuracy();
+end
+
+accuracies'
+fprintf('mean acc = %.2f\n',mean(accuracies));
\ No newline at end of file
diff --git a/doc/exampleEarlyFusion.html b/doc/exampleEarlyFusion.html
index 2ac0e86..5e0bcb4 100644
--- a/doc/exampleEarlyFusion.html
+++ b/doc/exampleEarlyFusion.html
@@ -118,6 +118,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0063 <span class="comment">%get the configuration used (for reporting)</span>
 0064 experiment.getExperimentInfo
 0065 experiment.getTime</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleEpoc.html b/doc/exampleEpoc.html
index de952b2..2b52e20 100644
--- a/doc/exampleEpoc.html
+++ b/doc/exampleEpoc.html
@@ -101,6 +101,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0051 <span class="comment">%get the configuration used (for reporting)</span>
 0052 <span class="comment">% experiment.getExperimentInfo</span>
 0053 <span class="comment">% experiment.getTime</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleITCCA.html b/doc/exampleITCCA.html
index 8433f34..f2cd1fd 100644
--- a/doc/exampleITCCA.html
+++ b/doc/exampleITCCA.html
@@ -85,6 +85,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0040         
 0041     <span class="keyword">end</span>
 0042 <span class="keyword">end</span></pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleL1MCCA.html b/doc/exampleL1MCCA.html
index 511922c..ba0115b 100644
--- a/doc/exampleL1MCCA.html
+++ b/doc/exampleL1MCCA.html
@@ -84,6 +84,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0039 accuracies'
 0040 <span class="comment">%mean accuracy for all subjects</span>
 0041 fprintf(<span class="string">'mean acc = %.2f\n'</span>, mean(accuracies));</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleLSL.html b/doc/exampleLSL.html
index d086b38..df7ea66 100644
--- a/doc/exampleLSL.html
+++ b/doc/exampleLSL.html
@@ -104,6 +104,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0058 <span class="comment">%Run the recognition task. The task runs indefinetely until is specifically</span>
 0059 <span class="comment">%interrupted</span>
 0060 lsl.runSSVEP(eventCode);</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleLateFusion.html b/doc/exampleLateFusion.html
index 19913ed..043b18a 100644
--- a/doc/exampleLateFusion.html
+++ b/doc/exampleLateFusion.html
@@ -121,6 +121,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0066 <span class="comment">%get the configuration used (for reporting)</span>
 0067 experiment.getExperimentInfo
 0068 experiment.getTime</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleMotorPWelch.html b/doc/exampleMotorPWelch.html
index a690fd6..00086cc 100644
--- a/doc/exampleMotorPWelch.html
+++ b/doc/exampleMotorPWelch.html
@@ -78,6 +78,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0033 experiment.run();
 0034 accuracy = experiment.results{1}.getAccuracy();
 0035</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleOptimal.html b/doc/exampleOptimal.html
index 5d10b31..b895dfb 100644
--- a/doc/exampleOptimal.html
+++ b/doc/exampleOptimal.html
@@ -102,6 +102,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0053 <span class="comment">%get the configuration used (for reporting)</span>
 0054 experiment.getExperimentInfo
 0055 experiment.getTime</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/exampleSMFA.html b/doc/exampleSMFA.html
index 8e07a8b..860897a 100644
--- a/doc/exampleSMFA.html
+++ b/doc/exampleSMFA.html
@@ -158,6 +158,6 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0113     subaccuracies(subn) = mean(accuracies);
 0114 <span class="keyword">end</span>
 0115 fprintf(<span class="string">'mean acc for all subjects %.2f\n'</span>,mean(subaccuracies));</pre></div>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:34 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:22 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file
diff --git a/doc/graph.dot b/doc/graph.dot
index c7af74f..d92e500 100644
--- a/doc/graph.dot
+++ b/doc/graph.dot
@@ -6,6 +6,7 @@ digraph m2html {
   exampleDefault [URL="exampleDefault.html"];
   exampleEPOCCCASVM [URL="exampleEPOCCCASVM.html"];
   exampleERRP [URL="exampleERRP.html"];
+  exampleERRPSSVEPDemo [URL="exampleERRPSSVEPDemo.html"];
   exampleEarlyFusion [URL="exampleEarlyFusion.html"];
   exampleEpoc [URL="exampleEpoc.html"];
   exampleITCCA [URL="exampleITCCA.html"];
diff --git a/doc/graph.html b/doc/graph.html
index ba4db20..c7461e9 100644
--- a/doc/graph.html
+++ b/doc/graph.html
@@ -24,18 +24,19 @@ <h1>Dependency Graph for .</h1>
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-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:21 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
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diff --git a/doc/graph.map b/doc/graph.map
index c98355c..4d340f9 100644
--- a/doc/graph.map
+++ b/doc/graph.map
@@ -3,12 +3,13 @@
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diff --git a/doc/index.html b/doc/index.html
index 095abe2..6a2bf0a 100644
--- a/doc/index.html
+++ b/doc/index.html
@@ -19,7 +19,7 @@ <h1>Index for .</h1>
 
 <h2>Matlab files in this directory:</h2>
 <table>
-<tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCSP.html">exampleCSP</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCombiCCA.html">exampleCombiCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleDefault.html">exampleDefault</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEPOCCCASVM.html">exampleEPOCCCASVM</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleERRP.html">exampleERRP</a></td><td>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter'); </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEarlyFusion.html">exampleEarlyFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEpoc.html">exampleEpoc</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleITCCA.html">exampleITCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleL1MCCA.html">exampleL1MCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLSL.html">exampleLSL</a></td><td>Add dependencies to the Matlab path, LibLSL is required for this example </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLateFusion.html">exampleLateFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleMotorPWelch.html">exampleMotorPWelch</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleOptimal.html">exampleOptimal</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleSMFA.html">exampleSMFA</a></td><td> </td></tr></table>
+<tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCSP.html">exampleCSP</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleCombiCCA.html">exampleCombiCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleDefault.html">exampleDefault</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEPOCCCASVM.html">exampleEPOCCCASVM</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleERRP.html">exampleERRP</a></td><td>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter'); </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleERRPSSVEPDemo.html">exampleERRPSSVEPDemo</a></td><td>d2 = designfilt('bandpassiir', 'SampleRate', 256, 'FilterOrder', 8 ,'HalfPowerFrequency1', 1, 'HalfPowerFrequency2', 10,'DesignMethod', 'butter'); </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEarlyFusion.html">exampleEarlyFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleEpoc.html">exampleEpoc</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleITCCA.html">exampleITCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleL1MCCA.html">exampleL1MCCA</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLSL.html">exampleLSL</a></td><td>Add dependencies to the Matlab path, LibLSL is required for this example </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleLateFusion.html">exampleLateFusion</a></td><td>Leave one subject out testing </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleMotorPWelch.html">exampleMotorPWelch</a></td><td> </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleOptimal.html">exampleOptimal</a></td><td>Load the data. Call this once outside of the script so you dont have to </td></tr><tr><td><img src="../matlabicon.gif" alt="" border="">&nbsp;<a href="exampleSMFA.html">exampleSMFA</a></td><td> </td></tr></table>
 
 
 <h2>Subsequent directories:</h2>
@@ -29,6 +29,6 @@ <h2>Dependency Graph</h2>
 <ul style="list-style-image:url(../simulinkicon.gif)">
 <li>View the <a href="graph.html">Graph</a>.</li>
 </ul>
-<hr><address>Generated on Fri 25-Nov-2016 14:50:32 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 25-Nov-2016 17:12:20 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file