DocumentCode
1468787
Title
Quasi-nonparametric blind inversion of Wiener systems
Author
Taleb, Anisse ; Solé, Jordi ; Jutten, Christian
Author_Institution
Sch. of Electr. & Comput. Eng. Sci., Curtin Univ. of Technol., Perth, WA, Australia
Volume
49
Issue
5
fYear
2001
fDate
5/1/2001 12:00:00 AM
Firstpage
917
Lastpage
924
Abstract
An efficient procedure for the blind inversion of a nonlinear Wiener system is proposed. We show that the problem can be expressed as a problem of blind source separation in nonlinear mixtures for which a solution has been previously proposed. Based on a quasi-nonparametric relative gradient descent, the proposed algorithm can perform efficiently even in the presence of hard distortions
Keywords
Wiener filters; filtering theory; gradient methods; identification; inverse problems; nonlinear filters; optimisation; Monte-Carlo simulations; Wiener filter; blind source separation; cost function optimization algorithm; hard distortions; mutual information; nonlinear Wiener system; nonlinear mixtures; quasi-nonparametric blind inversion; quasi-nonparametric relative gradient descent; Australia; Biological system modeling; Cost function; Mathematical model; Mutual information; Nonlinear distortion; Nonlinear filters; Nonlinear systems; Power system modeling; Signal processing algorithms;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.917796
Filename
917796
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