MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization
نویسندگان
چکیده
منابع مشابه
MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and ℓ1-Norm Minimization
We address the problem of underdetermined BSS. While most previous approaches are designed for instantaneous mixtures, we propose a time-frequency-domain algorithm for convolutive mixtures. We adopt a two-step method based on a general maximum a posteriori (MAP) approach. In the first step, we estimate the mixing matrix based on hierarchical clustering, assuming that the source signals are suff...
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There are very few techniques that can separate signals from the convolutive mixture in the underdetermined case. We have developed a method that uses overcomplete expansion of the signal created with a time-frequency transform and that also uses the property of sparseness and a Laplacian source density model to obtain the source signals from the instantaneously mixed signals in the underderdet...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2006
ISSN: 1687-6180
DOI: 10.1155/2007/24717