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EEG signal denoising based on a wavelet nonlinear continuous function |
YU Xiang-yang,LUO Zhi-zeng |
Robot Research Institute, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China |
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Abstract The environmental noise and frequency noise interference on EEG for further processing and analysis with the extremely disadvantageous influence. In view of the traditional wavelet coefficients by soft threshold de noise processing method of waveform distortion and hard threshold de noise processing method after the oscillation phenomenon, put forward a new wavelet coefficients nonlinear continuous function attenuation processing algorithm. By means of the wavelet coefficients of the nonlinear attenuation process, the low values of a continuous function between the end of wavelet coefficients between hard and soft threshold, effectively avoid the waveform distortion and oscillation. Processed EEG signal to noise ratio and mean square error are superior to the traditional wavelet denoising processing method.
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Received: 23 June 2016
Published: 27 September 2017
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