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| HAL : inria-00537756, version 1 |
| Voir la fiche détaillée |  BibTeX,EndNote,... |
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| Latent Variable Analysis and Signal Separation, 9th International Conference on (LVA/ICA2010), St Malo : France (2010) |
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| Double Sparsity: Towards Blind Estimation of Multiple Channels |
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| Prasad Sudhakar 1Simon Arberet 2 |
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| (09/2010) |
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| We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources in the time-frequency domain. The proposed framework includes two steps: (a) a clustering step, to determine the frequencies where each source is active alone; (b) a filter estimation step, to recover the filter associated to each source from the corresponding incomplete frequency information. We show how to solve the filter estimation step (b) using convex programming, and we explore numerically the factors that drive its performance. Step (a) remains challenging, and we discuss possible strategies that will be studied in future work. |
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| 1 : | METISS (INRIA - IRISA) |
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CNRS : UMR6074 – INRIA – Institut National des Sciences Appliquées (INSA) - Rennes – Université de Rennes 1 |
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| 2 : | Ecole Polytechnique Fédérale de Lausanne (EPFL) |
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École Polytechnique Fédérale de Lausanne |
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| Domaine | : | Informatique/Traitement du signal et de l'image Sciences de l'ingénieur/Traitement du signal et de l'image |
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| blind filter estimation – sparsity – convex optimisation |
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| Liste des fichiers attachés à ce document : | |||||
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| inria-00537756, version 1 | |
| http://hal.inria.fr/inria-00537756 | |
| oai:hal.inria.fr:inria-00537756 | |
| Contributeur : Rémi Gribonval | |
| Soumis le : Lundi 22 Novembre 2010, 09:34:03 | |
| Dernière modification le : Mercredi 1 Décembre 2010, 16:13:23 | |
