0505138 20240111141019.820190603235959.9 85069501261 000482554005104 10.1109/ICASSP.2019.8683885 Performance bound for blind extraction of non-Gaussian complex-valued vector component from Gaussian background 5 s. C cav_un_epca*0505137978-1-4799-8130-42019 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 20195287-5291Brighton, UKIEEE2019 Blind Source Extraction Independent Component Analysis Independent Vector Analysis cav_un_auth*0355383 40 Kautský Václav UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0230113 30 Koldovský Z. CZ cav_un_auth*0101212 30 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. http://library.utia.cas.cz/separaty/2019/SI/tichavsky-0505138.pdf 343 kB cav_un_auth*0345929 GA17-00902S GA ČR Independent Vector Extraction aims at the joint blind source extraction of K dependent signals of interest (SOI) from K mixtures (one signal from one mixture). Similarly to Independent Component/Vector Analysis (ICA/IVA), the SOIs are assumed to be independent of the other signals in the mixture. Compared to IVA, the (de-)mixing IVE model is reduced in the number of parameters for the extraction problem. The SOIs are assumed to be non-Gaussian or noncircular Gaussian, while the other signals are modeled as circular Gaussian. In this paper, a Cramer-Rao-Induced Bound (CRIB) for the achievable Interference-to-Signal Ratio (ISR) is derived for IVE. The bound is compared with similar bounds for ICA, IVA, and Independent Component Extraction (ICE). Numerical simulations show a good correspondence between the empirical results and the theory. cav_un_auth*0375642 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2019 20190512 20190517 Brighton GB BB 20000 20200 20205 2020 3 PO RVO:67985556 http://hdl.handle.net/11104/0297073 S 3+4 Article Chemistry Physical|Nanoscience Nanotechnology|Materials Science Multidisciplinary|Physics Atomic Molecular Chemical 2019 85069501261 SCOPUS PUBMED 000482554005104 WOS 343 kB cav_un_epca*0505137 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2019 978-1-4799-8130-4 5287 5291 Brighton, UK IEEE 2019 CFP19ICA-USB