A Mathematical Model of Authentication under Normal State EEG

Abstract

Wavelet decomposition is a commonly used data analysis model, but the wavelet decomposition can be used to do EEG signal identification, less relevant research, this article from the wavelet decomposition of the mathematical principles, establishment mathematical model of authentication under normal state EEG, and experimental design, verification. one of the selected on the basis of identity certification tool is difficult to counterfeit, studies show that EEG signal is very difficult to forge, in a certain period of time study, the use of special stimulating EEG signals collected can be used as identification tool, EEG under normal state is used as identification tool? This paper from the average recognition rate and the average error rate of 15 of the subjects of EEG signals, the results show that the use of own EEG signal, the subjects can identify the very good, but the average error rate results show that, the method of noise of the poor rate of EEG recognition, in order to improve the efficiency of recognition this paper respectively for1second, 2 second, 3 seconds to 4 seconds and 5 seconds of EEG data were studied, results showed that knowledge is not the signal interception time is longer, the better the results, when the recognition rate is up to a certain extent, time is long, the recognition rate will decline.