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dc.contributor.authorCharalambous, Charalambos D.en
dc.contributor.authorElliott, Robert J.en
dc.contributor.authorKrishnamurthy, Vikramen
dc.creatorCharalambous, Charalambos D.en
dc.creatorElliott, Robert J.en
dc.creatorKrishnamurthy, Vikramen
dc.description.abstractIn this paper 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.en
dc.sourceProceedings of the IEEE Conference on Decision and Controlen
dc.sourceProceedings of the IEEE Conference on Decision and Controlen
dc.subjectRandom processesen
dc.subjectDifferentiation (calculus)en
dc.subjectIntegral equationsen
dc.subjectParameter estimationen
dc.subjectNonlinear control systemsen
dc.subjectControl system analysisen
dc.subjectPartial differential equationsen
dc.subjectConditional moment generating functionsen
dc.subjectContinuous time nonlinear systemsen
dc.subjectGaussian densitiesen
dc.titleConditional moment generating functions for integrals and stochastic integralsen
dc.description.endingpage3949Πολυτεχνική Σχολή / Faculty of EngineeringΤμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering
dc.type.uhtypeConference Objecten
dc.contributor.orcidCharalambous, Charalambos D. [0000-0002-2168-0231]

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