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Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions

Abstract:

In this paper, we present an efficient particle filtering method to perform optimal estimation in jump Markov (nonlinear) systems (JMSs). Such processes consist of a mixture of heterogeneous models and possess a natural hierarchical structure. We take advantage of these specificities in order to develop a generic filtering methodology for these models. The method relies on an original and nontrivial combination of techniques that have been presented recently in the filtering literature, namel...

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Publication status:
Published

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Publisher copy:
10.1109/TSP.2003.810284

Authors


Andrieu, C More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Journal:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume:
51
Issue:
7
Pages:
1762-1770
Publication date:
2003-07-05
DOI:
ISSN:
1053-587X
URN:
uuid:afb35728-1797-4572-93fd-507b035001a1
Source identifiers:
190601
Local pid:
pubs:190601

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