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Iterative algorithms for state estimation of jump Markov linear systems

Abstract:

Jump Markov linear systems (JMLS) 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. In this paper, we present original deterministic and stochastic iterative algorithms for optimal state estimation of JMLSs. The first stochastic algorithm yields minimum mean square error (MMSE) estimates of the f...

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Publication status:
Published

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Publisher copy:
10.1109/78.923304

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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Role:
Author
Journal:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume:
49
Issue:
6
Pages:
1216-1227
Publication date:
2001-06-05
DOI:
ISSN:
1053-587X
URN:
uuid:46a3de49-dac0-4180-9d67-ded9bc52d053
Source identifiers:
190616
Local pid:
pubs:190616

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