Discrete-time expectation maximization algorithms for Markov-modulated poisson processes
Date
2008
Authors
Elliott, R.
Malcolm, W.
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Advisors
Journal Title
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Volume Title
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Journal article
Citation
IEEE Transactions on Automatic Control, 2008; 53(2):247-256
Statement of Responsibility
Elliott, R.J. and Malcolm, W.P.
Conference Name
Abstract
In this paper, we consider parameter estimation Markov-modulated Poisson processes via robust filtering and smoothing techniques. Using the expectation maximization algorithm framework, our filters and smoothers can be applied to estimate the parameters of our model in either an online configuration or an offline configuration. Further, our estimator dynamics do not involve stochastic integrals and our new formulas, in terms of time integrals, are easily discretized, and are written in numerically stable forms in W. P. Malcolm, R. J. Elliott, and J. van der Hoek, ldquoOn the numerical stability of time-discretized state estimation via clark transformations,rdquo presented at the IEEE Conf. Decision Control, Mauii, HI, Dec. 2003.
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Dissertation Note
Provenance
Description
Link to a related website: https://prism.ucalgary.ca/bitstream/1880/49072/1/Elliott_Discrete_Time_Expectation_2008_postprint.pdf, Open Access via Unpaywall
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Rights
Copyright 2008 IEEE