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Evaluation of likelihood functions

dc.contributor.authorDuncan, Tyrone E.en_US
dc.date.accessioned2006-04-17T15:27:35Z
dc.date.available2006-04-17T15:27:35Z
dc.date.issued1968-07en_US
dc.identifier.citationDuncan, Tyrone E. (1968/07)."Evaluation of likelihood functions." Information and Control 13(1): 62-74. <http://hdl.handle.net/2027.42/33137>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B7MFM-4DX41CK-64/2/c6729ae241ad6198117e0b2d6ff0a61aen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/33137
dc.description.abstractAn expression is obtained for the likelihood function for the detection of a stochastic signal (diffusion process) in white noise. A stochastic differential equation is then obtained for the evolution of the likelihood function and the coefficients of this differential equation are related to a corresponding nonlinear filtering problem. Some extensions are noted to diffusion process signals in correlated noise and to more general stochastic signals.en_US
dc.format.extent588700 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleEvaluation of likelihood functionsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbsecondlevelInformation and Library Scienceen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumInformation and Control Engineering, The University of Michigan, Ann Arbor, Michigan 48104, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/33137/1/0000523.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/S0019-9958(68)90795-Xen_US
dc.identifier.sourceInformation and Controlen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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