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Approximate Maximum Likelihood Source Separation Using the Natural Gradient
Seungjin CHOI Andrzej CICHOCKI Liqing ZHANG Shun-ichi AMARI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2003/01/01
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Digital Signal Processing
independent component analysis, maximum likelihood estimation, natural gradient, source separation, overdetermined mixtures,
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This paper addresses a maximum likelihood method for source separation in the case of overdetermined mixtures corrupted by additive white Gaussian noise. We consider an approximate likelihood which is based on the Laplace approximation and develop a natural gradient adaptation algorithm to find a local maximum of the corresponding approximate likelihood. We present a detailed mathematical derivation of the algorithm using the Lie group invariance. Useful behavior of the algorithm is verified by numerical experiments.