Estimation of Hidden Markov Models

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dc.contributor.authorRamezani, Vahid Rezaen_US
dc.contributor.authorMarcus, Steven I.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:10:38Z
dc.date.available2007-05-23T10:10:38Z
dc.date.issued2001en_US
dc.description.abstractA risk-sensitive generalization of the Maximum A Posterior Probability (MAP) estimationfor partially observed Markov chains is presented.Using a change of measure technique,a cascade filtering scheme for the risk-sensitivestate estimation is introduced. Structural results,the influence of the availability of information, mixing and non-mixingdynamics, and the connection with other risk-sensitive estimation methodsare considered. A qualitative analysis of the samplepaths clarifies the underlying mechanism.en_US
dc.format.extent344121 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6196
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2001-21en_US
dc.subjectSensor-Actuator Networksen_US
dc.titleEstimation of Hidden Markov Modelsen_US
dc.typeTechnical Reporten_US

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