Počet záznamů: 1
Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources
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SYSNO ASEP 0480768 Druh ASEP V - Výzkumná zpráva Zařazení RIV O - Ostatní Název Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources Tvůrce(i) Šembera, Ondřej (UTIA-B)
Tichavský, Petr (UTIA-B) RID, ORCID
Koldovský, Zbyněk (UTIA-B) RIDVyd. údaje Praha: ÚTIA AV ČR v.v.i, 2016 Edice Research Report Č. sv. edice 2360 Poč.str. 10 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. CZ - Česká republika Klíč. slova blind separation ; algorithms ; block gaussian separation Vědní obor RIV BI - Akustika a kmity Obor OECD Acoustics CEP FV10645 GA MPO - Ministerstvo průmyslu a obchodu Institucionální podpora UTIA-B - RVO:67985556 Anotace In many applications, there is a need to blindly separate independent sources from their linear instantaneous mixtures while the mixing matrix or source properties are slowly or abruptly changing in time. The easiest way to separate the data is to consider off-line estimation of the model parameters repeatedly in time shifting window. Another popular method is the stochastic natural gradient algorithm, which relies on non-Gaussianity of the separated signals and is adaptive by its nature. In this paper, we propose an adaptive version of two blind source separation algorithms which exploit non-stationarity of the original signals. The results indicate that the proposed algorithms slightly outperform the natural gradient in the trade-off between the algorithm’s ability to quickly adapt to changes in the mixing matrix and the variance of the estimate when the mixing is stationary. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2018
Počet záznamů: 1