Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00480768" target="_blank" >RIV/67985556:_____/16:00480768 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources
Original language description
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.
Czech name
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Czech description
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Project
<a href="/en/project/FV10645" target="_blank" >FV10645: The continuous acoustic emission analyzer for diagnostics of erosion-corrosion and creep damage of pipeline systems</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
U - Předmět řešení projektu je utajovanou skutečností podle zvláštních právních předpisů nebo je skutečností, jejíž zveřejnění by mohlo ohrozit činnost zpravodajské služby. Údaje o projektu jsou upraveny tak, aby byly zveřejnitelné

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