0478273 20240111140946.220170921235959.9 85041459923 000426986000233 10.23919/EUSIPCO.2017.8081389 6 s. C cav_un_epca*0478272978-0-9928626-7-11195-1199AthenyEURASIP2017 signals algorithms non-Gaussian distribution cav_un_auth*0230113 Koldovský Z. CZ cav_un_auth*0101212 Tichavský Petr UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0350114 Kautský V. CZ http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0478273.pdf 132 kB cav_un_auth*0345929 GA17-00902S GA ČR We propose a novel technique for the extraction of one independent component from an instantaneous linear complex-valued mixture of signals. The mixing model is optimized in terms of the number of parameters that are necessary to simultaneously estimate one column of the mixing matrix and one row of the de-mixing matrix, which both correspond to the desired source. The desired source is assumed to have a non-Gaussian distribution, while the other sources are modeled, for simplicity, as Gaussian-distributed, although in applications the other sources can be arbitrary. We propose an algorithm that can be interpreted as a blind self-steering Minimum-Power Distortionless Response (MPDR) beamformer. The method is compared with the popular Natural Gradient algorithm for general Independent Component Analysis. Their performances are comparable but the proposed method has a lower computational complexity, in examples, it is about four times faster. cav_un_auth*0350050 EUSIPCO 2017 - 25th European Signal Processing Conference 20170828 20170902 Kos GR BB 10000 10100 10103 2018 3 PR RVO:67985556 http://hdl.handle.net/11104/0274425 S RIV/67985556:_____/17:00478273!RIV18-AV0-67985556 191975691 Doplnění UT WOS, Scopus a DOI RIV/67985556:_____/17:00478273!RIV18-GA0-67985556 191965027 Doplnění UT WOS, Scopus a DOI n.a. Proceedings Paper Engineering Electrical Electronic|Telecommunications 2017 85041459923 SCOPUS PUBMED 000426986000233 WOS 132 kB cav_un_epca*0478272 Proceedings of the 25th European Signal Processing Conference (EUSIPCO 2017) 978-0-9928626-7-1 1195 1199 Atheny EURASIP 2017