Conditional moment generating functions for integrals and stochastic integrals

TitleConditional moment generating functions for integrals and stochastic integrals
Publication TypeConference Paper
Year of Publication1997
AuthorsCharalambous, C. D., R. J. Elliott, and V. Krishnamurthy
Conference NameDecision and Control, 1997., Proceedings of the 36th IEEE Conference on
Pagination3944 -3949 vol.4
Date Publisheddec.
Keywordsconditional moment generating functions, continuous time systems, continuous-time nonlinear systems, expectation maximization algorithm, filtering theory, Gaussian densities, Gaussian systems, integral equations, Kalman filters, matrix algebra, nonlinear control systems, parameter dependent ordinary stochastic differential equations, partial differential equations, recursive stochastic partial differential equations, state estimation, stochastic integrals, stochastic processes
Abstract

We present two methods for computing filtered estimates for moments of integrals and stochastic integrals of continuous-time nonlinear systems. The first method utilizes recursive stochastic partial differential equations. The second method utilizes conditional moment generating functions. For the case of Gaussian systems the recursive computations involve integrations with respect to Gaussian densities, while the moment generating functions involve differentiations of parameter dependent ordinary stochastic differential equations. The second method is applied in the expectation maximization algorithm

URLhttp://dx.doi.org/10.1109/CDC.1997.652479
DOI10.1109/CDC.1997.652479

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