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ICA Papers Classified According to their Applications and Performances
Ali MANSOUR Mitsuru KAWAMOTO
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2003/03/01
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Blind Signal Processing: Independent Component Analysis and Signal Separation)
contrast function, Kullback divergence, mutual-information, likelihood maximization,
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Since the beginning of the last two decades, many researchers have been involved in the problem of Blind Source Separation (BSS). Whilst hundreds of algorithms have been proposed to solve BSS. These algorithms are well known as Independent Component Analysis (ICA) algorithms. Nowadays, ICA algorithms have been used to deal with various applications and they are using many performance indices. This paper is dedicated to classify the different algorithms according to their applications and performances.