Review article: Human scalp EEG processing: Various soft computing approaches
Applied Soft Computing
Hi-index | 0.00 |
In this paper, we explore the use of genetic algorithm (GA) to select a minimum number of channels that identifies individuals based on brain signals i.e. electroencephalogram (EEG). The fusion of GA with linear discriminant classifier shows that the identification performance of EEG signals from 40 subjects does not degrade when using 23 selected channels as compared to all the available 61 channels as studied previously. As the channel identification method by GA is general, it could be used in any feature reduction application.