Separation of the EEG Signal using Improved FastICA Based on Kurtosis Contrast Function
نویسنده
چکیده
Independent component analysis (ICA) is a computational method to solve blind source separation (BSS) problem. In this paper, an improved FastICA based on Kurtosis was proposed to separate EEG signal. It was adopted from the gradient descent algorithm to improve the converge rate. Improved FastICA method was applied to separate EEG signal from a patient who had epilepsy seizure. The separation results proved that the method was feasible and effective.
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تاریخ انتشار 2011