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Identification of j...
Identification of jump Markov linear models using particle filters
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- Svensson, Andreas (author)
- Uppsala universitet,Avdelningen för systemteknik,Reglerteknik,Avdelningen för systemteknik, Uppsala universitet, Sverige
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- Schön, Thomas B. (author)
- Uppsala universitet,Avdelningen för systemteknik,Reglerteknik,Avdelningen för systemteknik, Uppsala universitet, Sverige
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- Lindsten, Fredrik, 1984- (author)
- Avdelningen för systemteknik, Uppsala universitet, Sverige
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(creator_code:org_t)
- Piscataway, NJ : IEEE, 2014
- 2014
- English.
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In: Proceedings of the 53rd IEEE Conference on Decision and Control. - Piscataway, NJ : IEEE. - 9781467360906 - 9781479977468 - 9781479977451 ; , s. 6504-6509
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Abstract
Subject headings
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- Jump Markov linear models consists of a finite number of linear state space models and a discrete variable encoding the jumps (or switches) between the different linear models. Identifying jump Markov linear models makes for a challenging problem lacking an analytical solution. We derive a new expectation maximization (EM) type algorithm that produce maximum likelihood estimates of the model parameters. Our development hinges upon recent progress in combining particle filters with Markov chain Monte Carlo methods in solving the nonlinear state smoothing problem inherent in the EM formulation. Key to our development is that we exploit a conditionally linear Gaussian substructure in the model, allowing for an efficient algorithm.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Publication and Content Type
- ref (subject category)
- kon (subject category)
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