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Evolution equations for Markov processes: Application to the white-noise theory of filtering

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Abstract

LetX be a Markov process taking values in a complete, separable metric spaceE and characterized via a martingale problem for an operatorA. We develop a criterion for invariant measures when rangeA is a subset of continuous functions onE. Using this, uniqueness in the class of all positive finite measures of solutions to a (perturbed) measure-valued evolution equation is proved when the test functions are taken from the domain ofA. As a consequence, it is shown that in the characterization of the optimal filter (in the white-noise theory of filtering) as the unique solution to an analogue of Zakai (as well as Fujisaki-Kallianpur-Kunita) equation, it suffices to take domainA as the class of test functions where the signal process is the solution to the martingale problem forA.

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The research of A. G. Bhatt was supported by the National Board for Higher Mathematics, Bombay, India. Part of this work was done while R. L. Karandikar was visiting Erasmus University, Rotterdam, The Netherlands.

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Bhatt, A.G., Karandikar, R.L. Evolution equations for Markov processes: Application to the white-noise theory of filtering. Appl Math Optim 31, 327–348 (1995). https://doi.org/10.1007/BF01215995

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