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Performance Bounds for Complex-Valued Independent Vector Analysis
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SYSNO ASEP 0531483 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Performance Bounds for Complex-Valued Independent Vector Analysis Author(s) Kautský, V. (CZ)
Tichavský, Petr (UTIA-B) RID, ORCID
Koldovský, Z. (CZ)
Adali, T. (US)Number of authors 4 Source Title IEEE Transactions on Signal Processing - ISSN 1053-587X
Roč. 68, č. 1 (2020), s. 4258-4267Number of pages 10 s. Publication form Print - P Language eng - English Country US - United States Keywords Blind source separation ; independent component/vector analysis ; Cramér-Rao lower bound, Subject RIV JD - Computer Applications, Robotics OECD category Electrical and electronic engineering R&D Projects GA17-00902S GA ČR - Czech Science Foundation (CSF) Method of publishing Limited access Institutional support UTIA-B - RVO:67985556 UT WOS 000556759700004 EID SCOPUS 85089296542 DOI 10.1109/TSP.2020.3009507 Annotation Independent Vector Analysis (IVA) is a method for joint Blind Source Separation of multiple datasets with wide area of applications including audio source separation, biomedical data analysis, etc. In this paper, identification conditions and Cramér-Rao Lower Bound (CRLB) on the achievable accuracy are derived for the complex-valued case involving circular and non-circular signals and correlated and uncorrelated datasets.The identification conditions describe when independent sources can be separated from their linear mixture in the statistically consistent manner. The CRLB shows how non-Gaussianty, non-circularity of sources and statistical dependence between datasets influence the attainable separation accuracy. Examples presented in the experimental part confirm the validity of the CRLB. Also, they show certain gap between the attainable accuracy and performance of state-of-the-art algorithms,especially, in case of highlynon-circular signals. Hence, there is a room for possible improvements.
Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2021 Electronic address https://ieeexplore.ieee.org/document/9141450
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