Filters for estimating Markov modulated Poisson processes and image-enchanced tracking

TitleFilters for estimating Markov modulated Poisson processes and image-enchanced tracking
Publication TypeConference Paper
Year of Publication1995
AuthorsKrishnamurthy, V., and R. J. Elliot
Conference NameDecision and Control, 1995., Proceedings of the 34th IEEE Conference on
Pagination63 -68 vol.1
Date Publisheddec.
Keywordsfilter-based expectation-maximization algorithm, filtering theory, finite-dimensional innovations, identification, image enhancement, image-enchanced tracking, Markov modulated Poisson processes, Markov processes, maximum-likelihood parameter estimates, state estimation, statistical analysis, stochastic processes, tracking, Zakai filters
Abstract

We present algorithms for state and parameter estimation of Markov modulated Poisson processes (MMPP). We first derive finite dimensional innovations and Zakai filters for various statistics of a MMPP. Using these filters, a filter-based expectation-maximization algorithm is derived for computing maximum-likelihood parameter estimates. Finally we present an application of the techniques in image enchanced tracking

URLhttp://dx.doi.org/10.1109/CDC.1995.478569
DOI10.1109/CDC.1995.478569

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