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Weight adjusted tensor method for blind separation of underdetermined mixtures of nonstationary sources
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SYSNO ASEP 0356666 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Weight adjusted tensor method for blind separation of underdetermined mixtures of nonstationary sources Author(s) Tichavský, Petr (UTIA-B) RID, ORCID
Koldovský, Zbyněk (UTIA-B) RIDSource Title IEEE Transactions on Signal Processing - ISSN 1053-587X
Roč. 59, č. 3 (2011), s. 1037-1047Number of pages 11 s. Language eng - English Country US - United States Keywords blind source separation ; tensor decomposition ; Cramer-Rao lower bound Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA102/09/1278 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000287316500014 EID SCOPUS 79951643186 DOI 10.1109/TSP.2010.2096221 Annotation In this paper, a novel algorithm to blindly separate an instantaneous linear underdetermined mixture of nonstationary sources is proposed. The separation is based on the working assumption that the sources are piecewise stationary with a different variance in each block. It proceeds in two steps: (1) estimating the mixing matrix, and (2) computing the optimum beamformer in each block to maximize the signal-to-interference ratio of each separated signal. Estimating the mixing matrix is accomplished through a specialized tensor decomposition of the set of sample covariance matrices of the received mixture in each block. It utilizes optimum weighting, which allows statistically efficient (CRB attaining) estimation provided that the data obey the assumed Gaussian piecewise stationary model. In simulations, performance of the algorithm is successfully tested on blind separation of 16 speech signals from 9 linear instantaneous mixtures of these signals. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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