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Mixture estimation with state-space components and Markov model of switching
- 1.0392950 - ÚTIA 2014 RIV NL eng J - Journal Article
Nagy, Ivan - Suzdaleva, Evgenia
Mixture estimation with state-space components and Markov model of switching.
Applied Mathematical Modelling. Roč. 37, č. 24 (2013), s. 9970-9984. ISSN 0307-904X. E-ISSN 1872-8480
R&D Projects: GA TA ČR TA01030123
Institutional support: RVO:67985556
Keywords : probabilistic dynamic mixtures, * probability density function * state-space models * recursive mixture estimation * Bayesian dynamic decision making under uncertainty * Kerridge inaccuracy
Subject RIV: BC - Control Systems Theory
Impact factor: 2.158, year: 2013
http://library.utia.cas.cz/separaty/2013/AS/nagy-mixture estimation with state-space components and markov model of switching.pdf
The paper proposes a recursive algorithm for estimation of mixtures with state-space components and a dynamic model of switching. Bayesian methodology is adopted. The main features of the presented approach are: (i) recursiveness that enables a real-time performance of the algorithm; (ii) one-pass elaboration of the data sample; (iii) dynamic nature of the model of switching active components; (iv) orientation at explicit solutions with exploitation of numerical procedures only in those parts which cannot be computed analytically; (v) systematic approach to the Bayesian mixture estimation theory.
Permanent Link: http://hdl.handle.net/11104/0221975
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