Classiication of Electroencephalogram Using Artiicial Neural Networks

نویسنده

  • A Sergejew
چکیده

In this paper, we will consider the problem of classifying electroencephalogram (EEG) signals of normal subjects, and subjects suuering from psychiatric disorder, e.g., obsessive compulsive disorder, schizophrenia, using a class of artiicial neural networks, viz., multi-layer perceptron. It is shown that the multilayer perceptron is capable of classifying unseen test EEG signals to a high degree of accuracy.

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تاریخ انتشار 1994