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A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

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EEGLearn

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea. This code can be used to construct sequence of images from ongoing EEG activities and to classify between different cognitive states through recurrent-convolutional neural nets.

Dependencies

In order to run this code you need to install the following modules:

Numpy and Scipy (http://www.scipy.org/install.html)

Scikit-Learn (http://scikit-learn.org/stable/install.html)

Theano (http://deeplearning.net/software/theano/install.html)

Lasagne (http://lasagne.readthedocs.org/en/latest/user/installation.html)

#Reference

If you are using this code please cite our paper.

Bashivan, Pouya, et al. "Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks." arXiv preprint arXiv:1511.06448 (2015).

http://arxiv.org/abs/1511.06448

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A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

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