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Bayesian estimation of mixtures with dynamic transitions and known component parameters

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    0364115 - ÚTIA 2012 RIV CZ eng J - Článek v odborném periodiku
    Nagy, I. - Suzdaleva, Evgenia - Kárný, Miroslav
    Bayesian estimation of mixtures with dynamic transitions and known component parameters.
    Kybernetika. Roč. 47, č. 4 (2011), s. 572-594. ISSN 0023-5954
    Grant CEP: GA MŠMT 1M0572; GA TA ČR TA01030123; GA ČR GA102/08/0567
    Grant ostatní: Skoda Auto(CZ) ENS/2009/UTIA
    Výzkumný záměr: CEZ:AV0Z10750506
    Klíčová slova: mixture model * Bayesian estimation * approximation * clustering * classification
    Kód oboru RIV: BC - Teorie a systémy řízení
    Impakt faktor: 0.454, rok: 2011
    http://library.utia.cas.cz/separaty/2011/AS/nagy-bayesian estimation of mixtures with dynamic transitions and known component parameters.pdf

    Probabilistic mixtures provide flexible "universal" approximation of probability density functions. Their wide use is enabled by the availability of a range of efficient estimation algorithms. Among them, quasi-Bayesian estimation plays a prominent role as it runs "naturally" in one-pass mode. This is important in on-line applications and/or extensive databases. It even copes with dynamic nature of components forming the mixture. However, the quasi-Bayesian estimation relies on mixing via constant component weights. Thus, mixtures with dynamic components and dynamic transitions between them are not supported. The present paper fills this gap. For the sake of simplicity and to give a better insight into the task, the paper considers mixtures with known components. A general case with unknown components will be presented soon.
    Trvalý link: http://hdl.handle.net/11104/0199682

     
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