142-149 Neural Network Classification of Alcohol Abusers.PDF
نویسنده
چکیده
We propose a novel method to classify alcohol abusers. The method efficiently estimates total power in gamma band frequency (GBF) of multi-channel Visual Evoked Potential (VEP) signals in the time domain, circumventing power spectrum computation. These are used as features to classify alcohol abusers from control subjects with Multilayer PerceptronBackpropagation (MLP-BP) and Fuzzy ARTMAP (FA) neural network classifiers. Perfect classification performance obtained in the experimental study conducted with 20 subjects totaling 800 VEP signals validates the proposed method.
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تاریخ انتشار 2003