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Convergence of Nonlinear Filters for Randomly Perturbed Dynamical Systems

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Abstract

We establish convergence of the nonlinear filter of the state of a randomly perturbed dynamical system in which the perturbation is a rapidly fluctuating ergodic Markov process, and the observation process conditions the state of the system. The limiting nonlinear filter is completely characterized.

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Authors and Affiliations

  1. TD Securities, Toronto Dominion Bank, 14–18 Finsbury Square, London, EC2A 1DB, England

    Vladimir M. Lucic

  2. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada

    Andrew J. Heunis

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  1. Vladimir M. Lucic
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  2. Andrew J. Heunis
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Correspondence to Vladimir M. Lucic or Andrew J. Heunis.

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Lucic, V., Heunis, A. Convergence of Nonlinear Filters for Randomly Perturbed Dynamical Systems. Appl Math Optim 48, 93–128 (2003). https://doi.org/10.1007/s00245-003-0772-8

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  • DOI: https://doi.org/10.1007/s00245-003-0772-8

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