M. Esmaeili, Mohamad H. Jabalameli, Zeinab Moghadam
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引用次数: 7
Abstract
In this paper, dynamic synapse neural network (DSNN) has been applied to perform EEG signal recognition task. The wavelet packet transform is applied to the EEG signal in order to decompose it into frequency sub-bands, before being introduced to the neural network. In this study we have applied a genetic algorithm (GA) learning method with different fitness functions to optimize the neural network. The advantage of the GA method is that it facilitates finding of a semi-optimal parameter set in the search space domain. The network has been testes for EEG signals tat are provided from BCI Competition 2003 and the results show the power of DSNN in processing of noisy nature signals as EEG signals.
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