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
fDate :
5/1/2001 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
