Classification of EEG Signals from Four Subjects During Five Mental Tasks

Abstract

Neural networks are trained to classify half-second segments of six-channel, EEG data into one of five classes corresponding to five cognitive tasks performed by four subjects. Two and three-layer feedforward neural networks are trained using 10-fold cross-validation and early stopping to control over-fitting. EEG signals were represented as autoregressive… (More)

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@inproceedings{Anderson1996ClassificationOE, title={Classification of EEG Signals from Four Subjects During Five Mental Tasks}, author={Charles William Anderson}, year={1996} }