DocumentCode
3111344
Title
Approximate maximum likelihood source separation using the natural gradient
Author
Choi, Seungjin ; Cichocki, Andrzej ; Zhang, Liqing ; Amari, Shunichi
Author_Institution
Dept. of Comput. Sci. & Eng., POSTECH, South Korea
fYear
2001
fDate
2001
Firstpage
235
Lastpage
238
Abstract
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
Keywords
AWGN; approximation theory; gradient methods; maximum likelihood detection; optimisation; Laplace approximation; additive white Gaussian noise; approximate maximum likelihood source separation; maximization; natural gradient adaptation algorithm; objective function; overdetermined mixtures; Additive white noise; Artificial intelligence; Computer science; Context; Information systems; Maximum likelihood estimation; Signal processing; Signal processing algorithms; Source separation; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, 2001. (SPAWC '01). 2001 IEEE Third Workshop on Signal Processing Advances in
Conference_Location
Taiwan
Print_ISBN
0-7803-6720-0
Type
conf
DOI
10.1109/SPAWC.2001.923891
Filename
923891
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