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Cramer-Rao-Induced Bound for Interference-to-Signal Ratio Achievable through Non-Gaussian Independent Component Extraction
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SYSNO ASEP 0483429 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Cramer-Rao-Induced Bound for Interference-to-Signal Ratio Achievable through Non-Gaussian Independent Component Extraction Author(s) Kautský, V. (CZ)
Koldovský, Z. (CZ)
Tichavský, Petr (UTIA-B) RID, ORCIDNumber of authors 3 Source Title IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017 . - Piscataway : IEEE, 2017 - ISBN 978-1-5386-1250-7 Pages s. 94-97 Number of pages 4 s. Publication form Medium - C Action CAMSAP 2017 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Event date 10.12.2017 - 13.12.2017 VEvent location Curacao Country NL - Netherlands Event type WRD Language eng - English Country US - United States Keywords Independent Component Extraction ; Independent Component Analysis Subject RIV BB - Applied Statistics, Operational Research OECD category Statistics and probability R&D Projects GA17-00902S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000428438100041 EID SCOPUS 85048543492 DOI https://doi.org/10.1109/CAMSAP.2017.8313097 Annotation This paper deals with the Cramér-Rao Lower Bound (CRLB) for a novel blind source separation method called Independent Component Extraction (ICE). Compared to Independent Component Analysis (ICA), ICE aims to extract only one independent signal from a linear mixture. The target signal is assumed to be non-Gaussian, while the other signals, which are not separated, are modeled as a Gaussian mixture. A CRLBinduced Bound (CRIB) for Interference-to-Signal Ratio (ISR) is derived. Numerical simulations compare the CRIB with the performance of an ICA and an ICE algorithm. The results show good agreement between the theory and the empirical results. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2018
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