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Noisy Component Extraction (NoiCE)

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2 Author(s)
Wai Yie Leong ; Singapore Institute of Manufacturing Technology, Singapore, Singapore ; Danilo P. Mandic

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.

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IEEE Transactions on Circuits and Systems I: Regular Papers  (Volume:57 ,  Issue: 3 )