期刊
TRENDS IN COGNITIVE SCIENCES
卷 6, 期 2, 页码 59-64出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/S1364-6613(00)01813-1
关键词
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Independent component analysis (ICA) is a method for automatically identifying the underlying factors in a given data set. This rapidly evolving technique is currently finding applications in analysis of biomedical signals (e.g. ERP, EEG, fMRI, optical imaging), and in models of visual receptive fields and separation of speech signals. This article illustrates these applications, and provides an informal introduction to ICA.
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