0483429 - ÚTIA 2018 RIV US eng C - Conference Paper (international conference)
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]
R&D Projects: GA ČR GA17-00902S
Grant - others:ČVUT Praha(CZ) SGS15/214/OHK4/3T/14
Institutional support: RVO:67985556
Keywords : Independent Component Extraction * Independent Component Analysis
OECD category: Statistics and probability
Result website:
http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0483429.pdf

DOI: https://doi.org/10.1109/CAMSAP.2017.8313097

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.
Permanent Link: http://hdl.handle.net/11104/0278760