A Unifying Information-Theoretic Framework for ICA
This chapter shows that different theories recently proposed for ICA lead to the same iterative learning algorithm for blind separation of mixed independent sources. Those theories are reviewed and it is suggested that information theory can be used to unify several lines of research.
KeywordsMutual Information Blind Source Separation Contrast Function Blind Deconvolution Joint Entropy
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