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dc.contributor.authorBeutler, Frederick J. (Frederick Joseph)en_US
dc.contributor.authorDolivo,françois-Bernard.en_US
dc.date.accessioned2006-09-11T19:45:41Z
dc.date.available2006-09-11T19:45:41Z
dc.date.issued1976-03en_US
dc.identifier.citationDolivo, Francois B.; Beutler, Frederick J.; (1976). "Recursive integral equations for the detection of counting processes." Applied Mathematics & Optimization 3(1): 65-71. <http://hdl.handle.net/2027.42/48093>en_US
dc.identifier.issn1432-0606en_US
dc.identifier.issn0095-4616en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/48093
dc.description.abstractA recursive stochastic integral equation for the detection of counting processes is derived from a previously known formula [5] of the likelihood ratio. This is done quite simply by using a result due to Doléans-Dade [4] on the solution of stochastic integral equations.en_US
dc.format.extent411660 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Springer-Verlag New York Inc.en_US
dc.subject.otherSystems Theory, Controlen_US
dc.subject.otherMathematical and Computational Physicsen_US
dc.subject.otherMathematicsen_US
dc.subject.otherOptimizationen_US
dc.subject.otherCalculus of Variations and Optimal Controlen_US
dc.subject.otherNumerical and Computational Methodsen_US
dc.subject.otherMathematical Methods in Physicsen_US
dc.titleRecursive integral equations for the detection of counting processesen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation and Control Engineering Program, The University of Michigan, 48109, Ann Arbor, Michigan, USAen_US
dc.contributor.affiliationotherIBM Research Laboratory, Zurich, Switzerland; IBM Forschung Laboratorium, CH 8803, Rüschlitnou, Switzerlanden_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/48093/1/245_2005_Article_BF02106191.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF02106191en_US
dc.identifier.sourceApplied Mathematics & Optimizationen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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