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On convolutive Blind Source Separation in a noisy context and a total variation regularization

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Résumé

We propose a new strategy for improving classical Blind Source Separation (BSS) methods. This strategy consists in denois-ing both the observed signal and the estimated source signal , and is based on the minimization of regularized criterion which takes into account the Total Variation of the signal. We prove by the way that the method leads to a projection problem which is solved by means of projected gradient algorithm. The effectiveness and the robustness of the proposed separating process are shown on numerical examples.
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Dates et versions

hal-01812533 , version 1 (11-06-2018)

Identifiants

Citer

T.Z. Z Boulmezaoud, M. El Rhabi, H. Fenniri, E. Moreau. On convolutive Blind Source Separation in a noisy context and a total variation regularization. 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2010), Jun 2010, Marrakech, Morocco. ⟨10.1109/SPAWC.2010.5671015⟩. ⟨hal-01812533⟩
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