In this paper, we will consider the problem of classifying electroencephalogram (EEG) signals of normal subjects, and subjects suffering from psychiatric disorder, e.g., obsessive compulsive disorder, schizophrenia, using a class of artificial 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.
['Ah Chung Tsoi', 'Dhong Su So', 'Alex A. Sergejew']
Classification of Electroencephalogram using Artificial Neural Networks