DocumentCode
394658
Title
Normalised natural gradient algorithm for the separation of cyclostationary sources
Author
Jafari, M.G. ; Chambers, J.A.
Author_Institution
Centre for Digital Signal Process. Res., King´´s Coll., London, UK
Volume
5
fYear
2003
fDate
6-10 April 2003
Abstract
A normalised natural gradient algorithm (NGA) for the separation of cyclostationary source signals is proposed in this paper. It improves the convergence properties of the cyclostationary natural gradient algorithm (CSNGA) by employing a gradient adaptive learning rate whose value changes in response to some change in the filter parameters. Experimental results demonstrate the improved behaviour of the approach.
Keywords
adaptive filters; adaptive signal processing; convergence of numerical methods; gradient methods; learning (artificial intelligence); source separation; convergence properties; cyclostationary source signal separation; filter parameters; gradient adaptive learning rate; normalised natural gradient algorithm; Adaptive filters; Autocorrelation; Blind source separation; Convergence; Digital signal processing; Educational institutions; Performance analysis; Signal processing; Signal processing algorithms; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-7663-3
Type
conf
DOI
10.1109/ICASSP.2003.1199931
Filename
1199931
Link To Document