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Blind Separation of Piecewise Stationary NonGaussian Sources
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SYSNO ASEP 0332915 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Ostatní články Title Blind Separation of Piecewise Stationary NonGaussian Sources Title Slepá separace po částech stacionárních negaussovských zdrojů Author(s) Koldovský, Zbyněk (UTIA-B) RID
Málek, J. (CZ)
Tichavský, Petr (UTIA-B) RID, ORCID
Deville, Y. (FR)
Hosseini, S. (FR)Source Title Signal Processing. - : Elsevier - ISSN 0165-1684
Roč. 89, č. 12 (2009), s. 2570-2584Number of pages 15 s. Publication form www - www Language eng - English Country NL - Netherlands Keywords Independent component analysis ; blind source separation ; 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) DOI 10.1016/j.sigpro.2009.04.021 Annotation We address Independent Component Analysis (ICA) of piecewise stationary and nonGaussian signals and propose a novel ICA algorithm called Block EFICA that is based on this generalized model of signals. The method is a further extension of the popular nonGaussianity-based FastICA algorithm and of its recently optimized variant called EFICA. In contrast to these methods, Block EFICA is developed to effectively exploit varying distribution of signals, thus, also their varying variance in time (nonstationarity) or, more precisely, in time-intervals (piecewise stationarity). In theory, the accuracy of the method asymptotically approaches Cramer-Rao lower bound (CRLB) under common assumptions when variance of the signals is constant. On the other hand, the performance is practically close to the CLRB even when variance of the signals is changing. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2010
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