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ICA Papers Classified According to their Applications and Performances Ali MANSOUR Mitsuru KAWAMOTO Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E86-A No.3 pp.620-633 Publication Date: 2003/03/01 Online ISSN: DOI: Print ISSN: 0916-8508 Type of Manuscript: Special Section PAPER (Special Section on Blind Signal Processing: Independent Component Analysis and Signal Separation) Category: Reviews Keyword: contrast function, Kullback divergence, mutual-information, likelihood maximization, Full Text: PDF(331.3KB)>>
Summary: 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. | ||||||||||
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