Optimal input features selection of wavelet-based EEG signals using GA
We present a method of selecting optimal input features from wavelet coefficients of electroencephalogram (EEG) signals. A combination of genetic algorithm (GA) and artificial neural network (ANN) are used to select the relevant features. In this investigation, classification accuracy and the fracti...
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Format: | Conference or Workshop Item |
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2004
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