P300 Wave based Person Identification using LVQ Neural Network

Person identification technology has many applications. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for person identification. In this paper, a kind of event related potential-P300, is employed as the input of the identification system. Compared with the other EEG signal, the P300 wave is easier for the classifier to tell the difference between diverse individuals. Learning vector quantization (LVQ) neural network is used for the classifier to identify which individual the P300 wave belongs to. Moreover, a voting scheme is introduced into the identification process which significantly improves the identification performance.

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