Title :
Noisy Component Extraction (NoiCE)
Author :
Leong, Wai Yie ; Mandic, Danilo P.
Author_Institution :
Singapore Institute of Manufacturing Technology, Singapore, Singapore
fDate :
3/1/2010 12:00:00 AM
Abstract :
To achieve efficient blind source extraction (BSE) from noisy mixtures, we propose a noisy component extraction (NoiCE) algorithm that combines standard BSE and a cascaded nonlinear adaptive estimator. There are no assumptions of statistical independence, and also as a byproduct of BSE after deflation, we may also obtain asymptotic identification of the a prioriunknown observation noise sources. By yielding an asymptotically efficient estimator in the presence of an unknown observation noise, the proposed algorithm may also be viewed as a robust approach to NoiCE. Simulations on both synthetic and real-world data confirm the validity of the proposed algorithm in noisy mixing environments.
Keywords :
Adaptive cascaded nonlinear estimation; blind source extraction (BSE); blind source separation (BSS); noisy mixtures;
Journal_Title :
Circuits and Systems I: Regular Papers, IEEE Transactions on
DOI :
10.1109/TCSI.2009.2024988