Blind Separation of Sources: Methods, Assumptions and Applications
نویسندگان
چکیده
The blind separation of sources is a recent and important problem in signal processing. Since 1984 [1], it has been studied by many authors whilst many algorithms have been proposed. In this paper, the description of the problem, its assumptions, its currently applications and some algorithms and ideas are discussed. key words: independent component analysis (ICA), contrast function, Kullback-Leibner divergence, prediction error, subspace methods, decorrelation, high order statistics, whitening, Mutual-Information, likelihood maximization, conjoint diagonalization.
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