计算机工程与应用2018，Vol.54Issue(10)：164-168,5.DOI:10.3778/j.issn.1002-8331.1612-0524
小波变换结合盲源分离的EEG情感识别
EEG emotion recognition based on blind source separation and wavelet
摘要
Abstract
The uncertainty of the EEG signals independent source number and other noise interference make the acquisi-tion of EEG signals between pilot signal crosstalk,noise source signal is difficult to estimate and mixed,seriously affect-ing the later analysis and research of EEG signals.The paper combines the wavelet transform with the blind source separa-tion algorithm,and rearranges the cross-term interference phenomenon of the Wigner distribution in the blind source sepa-ration 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 dis-tribution 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.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Key words
Electroencephalogram(EEG)/wavelet transform/blind source separation/rearranged smooth pseudo-Wigner distribution分类
信息技术与安全科学引用本文复制引用
沈成业,张雪英,孙颖,畅江..小波变换结合盲源分离的EEG情感识别[J].计算机工程与应用,2018,54(10):164-168,5.基金项目
国家自然科学基金(No.61371193). （No.61371193）
