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Approximate maximum likelihood source separation using the natural gradient

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4 Author(s)
Seungjin Choi ; Dept. of Comput. Sci. & Eng., POSTECH, South Korea ; Cichocki, A. ; Liqing Zhang ; Amari, S.

This paper addresses a maximum likelihood approach to source separation in the case of overdetermined mixtures corrupted by additive white Gaussian noise. We present an objective function that is an approximate likelihood function based on the Laplace approximation. Then we derive a natural gradient adaptation algorithm which maximizes the corresponding approximate likelihood function. Useful behavior of the proposed method is verified by numerical experiments

Published in:

Wireless Communications, 2001. (SPAWC '01). 2001 IEEE Third Workshop on Signal Processing Advances in

Date of Conference:

2001