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In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security problems of conventional biometric systems. In the present study, a novel EEG-based identification system with different entropy and a continuous convolution neural network (CNN) classifier is proposed. The performance of the proposed method is experimentally evaluated through the emotional EEG data. The conducted experiment shows that the proposeddoi:10.1155/2020/7574531 pmid:32849910 pmcid:PMC7439782 fatcat:7xemuoibjvbfdh7fp4b65vtebi