Title :
An RLS-Iterative Inversion Approach for Blind Signal Separation
Author :
Elsabrouty, Maha ; Bouchard, Martin ; Aboulnasr, Tyseer
Author_Institution :
Fac. of Inf. Eng. & Technol., German Univ. in Cairo
Abstract :
A new algorithm for blind signal separation that does not require pre-whitening is proposed in this paper. The algorithm is based on an iterative inversion of the mixing matrix. The algorithm is capable of working on-line and provides improved convergence speed and steady state error compared to the popular natural gradient algorithm, with a low additional computational cost
Keywords :
blind source separation; iterative methods; least squares approximations; matrix inversion; recursive estimation; RLS-iterative inversion approach; blind signal separation; convergence speed; mixing matrix inversion; natural gradient algorithm; steady state error; Blind source separation; Convergence; Cost function; Information theory; Iterative algorithms; Iterative methods; Maximum likelihood estimation; Signal processing; Signal processing algorithms; Source separation;
Conference_Titel :
Intelligent Signal Processing and Communications, 2006. ISPACS '06. International Symposium on
Conference_Location :
Yonago
Print_ISBN :
0-7803-9732-0
Electronic_ISBN :
0-7803-9733-9
DOI :
10.1109/ISPACS.2006.364802
