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Exact approximation of rao-blackwellised particle filters

Abstract:

Particle methods are a category of Monte Carlo algorithms that have become popular for performing inference in non-linear non-Gaussian state-space models. The class of "Rao-Blackwellised" particle filters exploits the analytic marginalisation that is possible for some statespace models to reduce the variance of the Monte Carlo estimates. Despite being applicable to only a restricted class of state-space models, such as conditionally linear Gaussian models, these algorithms have found numerous...

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Journal:
IFAC Proceedings Volumes (IFAC-PapersOnline) More from this journal
Volume:
16
Issue:
PART 1
Pages:
488-493
Publication date:
2012-01-01
DOI:
ISSN:
1474-6670
Language:
English
Keywords:
Pubs id:
pubs:354768
UUID:
uuid:a06101e8-089b-4dff-ab22-460e533168c2
Local pid:
pubs:354768
Source identifiers:
354768
Deposit date:
2013-11-16

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