On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering

We analyze the exponential stability properties of a class of measure-valued equations arising in nonlinear multi-target filtering problems. We also prove the uniform convergence properties w.r.t. the time parameter of a rather general class of stochastic filtering algorithms, including sequential M...

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Main Authors: Caron, F., Del Moral, P., Pace, M., Vo, Ba-Ngu
Format: Journal Article
Published: Taylor & Francis Inc. 2011
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/16151
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author Caron, F.
Del Moral, P.
Pace, M.
Vo, Ba-Ngu
author_facet Caron, F.
Del Moral, P.
Pace, M.
Vo, Ba-Ngu
author_sort Caron, F.
building Curtin Institutional Repository
collection Online Access
description We analyze the exponential stability properties of a class of measure-valued equations arising in nonlinear multi-target filtering problems. We also prove the uniform convergence properties w.r.t. the time parameter of a rather general class of stochastic filtering algorithms, including sequential Monte Carlo type models and mean field particle interpretation models. We illustrate these results in the context of the Bernoulli and the Probability Hypothesis Density filter, yielding what seems to be the first results of this kind in this subject.
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institution Curtin University Malaysia
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publishDate 2011
publisher Taylor & Francis Inc.
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spelling curtin-20.500.11937-161512018-03-29T09:06:10Z On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering Caron, F. Del Moral, P. Pace, M. Vo, Ba-Ngu Semigroup stability Functional contraction inequalities Nonlinear multi-target filtering Interacting particle systems Particle filters Probability hypothesis density filter Bernoulli filter We analyze the exponential stability properties of a class of measure-valued equations arising in nonlinear multi-target filtering problems. We also prove the uniform convergence properties w.r.t. the time parameter of a rather general class of stochastic filtering algorithms, including sequential Monte Carlo type models and mean field particle interpretation models. We illustrate these results in the context of the Bernoulli and the Probability Hypothesis Density filter, yielding what seems to be the first results of this kind in this subject. 2011 Journal Article http://hdl.handle.net/20.500.11937/16151 10.1080/07362994.2011.598797 Taylor & Francis Inc. restricted
spellingShingle Semigroup stability
Functional contraction inequalities
Nonlinear multi-target filtering
Interacting particle systems
Particle filters
Probability hypothesis density filter
Bernoulli filter
Caron, F.
Del Moral, P.
Pace, M.
Vo, Ba-Ngu
On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title_full On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title_fullStr On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title_full_unstemmed On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title_short On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering
title_sort on the stability and the approximation of branching distribution flows, with applications to nonlinear multiple target filtering
topic Semigroup stability
Functional contraction inequalities
Nonlinear multi-target filtering
Interacting particle systems
Particle filters
Probability hypothesis density filter
Bernoulli filter
url http://hdl.handle.net/20.500.11937/16151