DocumentCode :
465100
Title :
Noisy Component Extraction (Noice)
Author :
Leong, Wai Yie ; Mandic, Danilo P.
Author_Institution :
Dept. of Electron. & Electr. Eng., Imperial Coll. London
fYear :
2007
fDate :
27-30 May 2007
Firstpage :
3243
Lastpage :
3246
Abstract :
Existing blind source extraction (BSE) methods are limited to noise-free mixtures, which is not realistic. Based on a rigorous analysis of the existing BSE methods, we address the problem of noisy component extraction (NoiCE) which provides BSE in the presence of noise. As a byproduct in BSE after deflation, we may also obtain the asymptotic identification of the a priori unknown observation noise disturbance. By yielding an asymptotically efficient filter in the presence of an unknown observation noise, our approach may also be viewed as a robust approach to noisy component extraction. Simulation results are provided which confirm the validity of the theoretical results and demonstrate the performance of the derived algorithms in noisy mixing environments.
Keywords :
blind source separation; identification; mean square error methods; minimisation; NOICE; adaptive nonlinear prediction; asymptotic identification; asymptotically efficient filter; blind source extraction; blind source separation; noisy component extraction; noisy mixtures; unknown observation noise; Biomedical signal processing; Blind source separation; Covariance matrix; Educational institutions; Filters; Noise robustness; Radar signal processing; Signal processing algorithms; Source separation; Working environment noise; Blind source separation; adaptive nonlinear prediction; blind source extraction; noisy mixtures;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on
Conference_Location :
New Orleans, LA
Print_ISBN :
1-4244-0920-9
Electronic_ISBN :
1-4244-0921-7
Type :
conf
DOI :
10.1109/ISCAS.2007.378163
Filename :
4253370
Link To Document :
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