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Stochastic sampling algorithms for state estimation of jump Markov linear systems

Abstract:

Jump Markov linear systems are linear systems whose parameters evolve with time according to a finite-state Markov chain. Given a set of observations, our aim is to estimate the states of the finite-state Markov chain and the continuous (in space) states of the linear system. The computational cost in computing conditional mean or maximum a posteriori (MAP) state estimates of the Markov chain or the state of the jump Markov linear system grows exponentially in the number of observations. In t...

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Publication status:
Published

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Publisher copy:
10.1109/9.839943

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Logothetis, A More by this author
Krishnamurthy, V More by this author
Publisher:
IEEE
Journal:
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume:
45
Issue:
2
Pages:
188-202
Publication date:
2000-02-05
DOI:
ISSN:
0018-9286
URN:
uuid:b7014b39-c4c4-4d5c-b393-ad2af5167dae
Source identifiers:
190632
Local pid:
pubs:190632
Language:
English

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