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• W2078345072 abstract "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." @default.
• W2078345072 created "2016-06-24" @default.
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• W2078345072 date "2010-06-01" @default.
• W2078345072 modified "2023-09-23" @default.
• W2078345072 title "Robust Method via Independent Component Analysis with Additive Noise" @default.
• W2078345072 cites W2099741732 @default.
• W2078345072 doi "https://doi.org/10.4028/www.scientific.net/amr.113-116.272" @default.
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