Počet záznamů: 1  

Cramer-Rao-Induced Bound for Interference-to-Signal Ratio Achievable through Non-Gaussian Independent Component Extraction

  1. 1.
    0483429 - ÚTIA 2018 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
    Kautský, V. - Koldovský, Z. - Tichavský, Petr
    Cramer-Rao-Induced Bound for Interference-to-Signal Ratio Achievable through Non-Gaussian Independent Component Extraction.
    IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017. Piscataway: IEEE, 2017, s. 94-97. ISBN 978-1-5386-1250-7.
    [CAMSAP 2017 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. Curacao (NL), 10.12.2017-13.12.2017]
    Grant CEP: GA ČR GA17-00902S
    Grant ostatní: ČVUT Praha(CZ) SGS15/214/OHK4/3T/14
    Institucionální podpora: RVO:67985556
    Klíčová slova: Independent Component Extraction * Independent Component Analysis
    Obor OECD: Statistics and probability
    http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0483429.pdf

    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.
    Trvalý link: http://hdl.handle.net/11104/0278760

     
     
Počet záznamů: 1  

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