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- W2007448210 abstract "The problem of underdetermined blind audio source separation is usually addressed under the framework of sparse signal representation. In this paper, we develop a novel algorithm for this problem based on compressed sensing which is an emerging technique for efficient data reconstruction. The proposed algorithm consists of two stages. The unknown mixing matrix is firstly estimated from the audio mixtures in the transform domain, as in many existing methods, by a K-means clustering algorithm. Different from conventional approaches, in the second stage, the sources are recovered by using a compressed sensing approach. This is motivated by the similarity between the mathematical models adopted in compressed sensing and source separation. Numerical experiments including the comparison with a recent sparse representation approach are provided to showthe good performance of the proposed method." @default.
- W2007448210 created "2016-06-24" @default.
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- W2007448210 date "2009-08-01" @default.
- W2007448210 modified "2023-10-03" @default.
- W2007448210 title "A compressed sensing approach for underdetermined blind audio source separation with sparse representation" @default.
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- W2007448210 doi "https://doi.org/10.1109/ssp.2009.5278532" @default.
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