标题:Kurtosis Based Techniques for Signal Extraction
作者:Yongjian Zhao;Manlan Hao;
作者机构:[Yongjian Zhao]School of Information Engineering, Shandong University (weihai);[Manlan Hao]Wenshang County People's Hospital
来源:Proceedings of 2016 5th International Conference on Environment, Materials, Chemistry and Power Electronics(EMCPE 2016)
出版年:2016
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 simu...
资源类型:会议论文
原文链接:http://kns.cnki.net/kns/detail/detail.aspx?FileName=JKDZ201604002137&DbName=IPFD2017
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