how to implement neural network for eeg motor imagery classification?
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I extracted a 140x16 feature table with each line representing the feature vector of one experiment.Also i have the class labels of the 140 experiments.My intention is to use a neural network to classify my experiments by using half or a percentage of them for training the network and the rest for classification.Can anyone guide me?
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Accepted Answer
Greg Heath
on 3 Apr 2016
If you have c classes, the target columns should be columns of the c-dimension unit matrix eye(c).
[ I N ] = size(input) % [ 16 140 ]
[ c N ] = size(target) % [c 140 ]
For classification tutorials and examples search BOTH the NEWSREADER and ANSWERS with
greg patternnet
For documentation and associated unsatisfactory examples:
help patternnet
doc patternnet
Hope this helps.
Thank you for formally accepting my answer
Greg
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