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This paper presents a novel two-step approach for underdetermined blind source separation in the time-frequency domain. First, the single-source-points (SSPs), each of that is occupied by a single source, are detected through identifying the Time-Frequency (TF) points of observations using the complex value phase; the mixing matrix is then estimated accurately by employing K-means method among those...
Mixing matrix is the key issue in the under-determined blind source separation with sparse representation. The performance of traditional clustering method degrades when the sources do not satisfy W-disjoint orthogonal condition. This paper puts forward an effective method, which sets less condition on the sparseness of the sources, to improve the estimation of the mixing matrix. Firstly, we detect...
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