TY - GEN
T1 - Feedback particle filter for a continuous-time Markov chain
AU - Yang, Tao
AU - Mehta, Prashant G.
AU - Meyn, Sean P.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - This paper concerns approximation of Wonham's filter for estimating a continuous-time Markov chain, with continuous measurements corrupted by noise. The approximation is a new manifestation of the feedback particle filter (FPF) [15], [14], [13], a control-oriented approach for nonlinear filtering. A complete characterization of the feedback mechanism that defines the FPF is obtained, which leads to tractable algorithms for the nonlinear filtering problem, even for large state spaces. Numerical examples illustrate the application of these techniques.
AB - This paper concerns approximation of Wonham's filter for estimating a continuous-time Markov chain, with continuous measurements corrupted by noise. The approximation is a new manifestation of the feedback particle filter (FPF) [15], [14], [13], a control-oriented approach for nonlinear filtering. A complete characterization of the feedback mechanism that defines the FPF is obtained, which leads to tractable algorithms for the nonlinear filtering problem, even for large state spaces. Numerical examples illustrate the application of these techniques.
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M3 - Conference contribution
AN - SCOPUS:84883506944
SN - 9781479901777
T3 - Proceedings of the American Control Conference
SP - 6772
EP - 6777
BT - 2013 American Control Conference, ACC 2013
T2 - 2013 1st American Control Conference, ACC 2013
Y2 - 17 June 2013 through 19 June 2013
ER -