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EEG-signal-classification-using-basic-deep-learning-methods

The provided codes are developed firstly in the spring of 2016 then improved in the winter of 2016

Basic codes for reproducing the results in the paper:

Chu, L., Qiu, R., Liu, H., Ling, Z., Zhang, T., & Wang, J. (2017). Individual recognition in schizophrenia using deep learning methods with random forest and voting classifiers: Insights from resting state EEG streams. arXiv preprint arXiv:1707.03467.

If you get any question for our codes, please contact: leochu@sjtu.edu.cn or uestcahcl@gmail.com;

We are glad to help you processing massive streaming EEG data.

In this summer, we will provide an advanced verion of the codes, including some new methods we proposed to improve the generalization and representaion of the deep learning methods. The paper will be also renewed.

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Voted CNN for massive streaming EEG data classification

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