关键词: 脑电信号, 小波变换, 盲源分离, 重排光滑伪维格纳分布

Abstract: The uncertainty of the EEG signals independent source number and other noise interference make the acquisition of EEG signals between pilot signal crosstalk, noise source signal is difficult to estimate and mixed, seriously affecting the later analysis and research of EEG signals. The paper combines the wavelet transform with the blind source separation algorithm, and rearranges the cross-term interference phenomenon of the Wigner distribution in the blind source separation algorithm. The main idea of this experiment is to first carry out wavelet transform of each pilot signal, extract the characteristic wave of β wave, and then carry out blind source separation based on rearranged smooth pseudo-Wigner distribution for these β wave signals, and separate the correlation β wave component. The experimental results show that the method used in this paper separates the components of EEG signals with large correlation between them, and solves the problem that the source signal is difficult to estimate and so on, and makes the recognition result be improved obviously.

Key words: Electroencephalogram（EEG）, wavelet transform, blind source separation, rearranged smooth pseudo-Wigner distribution