标题:Robust Method via Independent Component Analysis with Additive Noise
作者:Zhao, Yongjian; Liu, Boqiang; Wang, Hongrun
通讯作者:Zhao, Y
作者机构:[Zhao, Yongjian] Shandong Univ, Inst Informat Engn, Weihai, Peoples R China.; [Zhao, Yongjian; Liu, Boqiang] Shandong Univ, Control Sci & Engn Inst, 更多
会议名称:International Conference of Environment Materials and Environment Management
会议日期:JUL 24-25, 2010
来源:ENVIRONMENT MATERIALS AND ENVIRONMENT MANAGEMENT PTS 1-3
出版年:2010
卷:113-116
页码:272-275
DOI:10.4028/www.scientific.net/AMR.113-116.272
关键词:ICA; Fast ICA algorithm; probability density function; estimator; ECG
摘要:Blind source separation via independent component analysis (ICA) has received increasing attention because of its potential application in signal processing system. The existing ICA methods can not give a consistent estimator of the mixing matrix because of additive noise. Based on interpretation and properties of the vectorial spaces of sources and mixtures, a new ICA method is presented in this paper that may constructively reject noise so as to estimate the mixing matrix consistently. This procedure may capture the underlying source dynamics effectively even if additive noise exists. The simulation results show that this method has high stability and reliability in the process of revealing the undering group structure of extracted ICA components.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650761184&doi=10.4028%2fwww.scientific.net%2fAMR.113-116.272&partnerID=40&md5=e9121f71fd9e0c26a41abc3d943fbad6
TOP