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An Novel Algorithm for Blind Source Separation with Unknown Sources Number.

Authors :
Wang, Jun
Yi, Zhang
Zurada, Jacek M.
Lu, Bao-Liang
Yin, Hujun
Ye, Ji-Min
Lou, Shun-Tian
Jin, Hai-Hong
Zhang, Xian-Da
Source :
Advances in Neural Networks - ISNN 2006; 2006, p1147-1152, 6p
Publication Year :
2006

Abstract

The natural gradient blind source separation (BSS) algorithm with unknown source number proposed by Cichocki in 1999 is justified in this paper. An new method to detect the redundant separated signals based on structure of separating matrix is proposed, by embedding it into the natural gradient algorithm, an novel BSS algorithm with an unknown source number is developed. The novel algorithm can successfully separate source signals and converge stably, while the Cichocki's algorithm would diverge inevitably. The new method embedded in novel algorithm can detect and cancel the redundant separated signals within 320 iteration, which is far quicker than the method based on the decorrelation, if some parameters are chosen properly. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540344391
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2006
Publication Type :
Book
Accession number :
32883784
Full Text :
https://doi.org/10.1007/11759966_169