标题:Kurtosis Based Techniques for Signal Extraction
作者:Zhao, Yongjian; Hao, Manlan
通讯作者:Zhao, YJ
作者机构:[Zhao, Yongjian] Shandong Univ Weihai, Sch Informat Engn, Weihai, Shandong, Peoples R China.; [Hao, Manlan] Wenshang Cty Peoples Hosp, Wenshang, Peo 更多
会议名称:5th International Conference on Environment, Materials, Chemistry and Power Electronics (EMCPE)
会议日期:APR 11-12, 2016
来源:PROCEEDINGS OF THE 2016 5TH INTERNATIONAL CONFERENCE ON ENVIRONMENT, MATERIALS, CHEMISTRY AND POWER ELECTRONICS
出版年:2016
卷:84
页码:673-676
关键词:Independence; Separation; Mixture; Source; Kurtosis
摘要:As a practical measure of non-Gaussianity, kurtosis generally represents the preferred technique for signal extraction. Here a learning rule is presented associated with kurtosis. It can recover one source signal owning the maximum absolute value of kurtosis among all original sources. Computer simulations on biomedical signals demonstrate its efficiency.
收录类别:CPCI-S
资源类型:会议论文
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