A Framework for Mixed Estimation of Hidden Markov Models

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dc.contributor.authorDey, Subhrakantien_US
dc.contributor.authorMarcus, Steven I.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:05:46Z
dc.date.available2007-05-23T10:05:46Z
dc.date.issued1998en_US
dc.description.abstractIn this paper, we present a framework for a mixed estimationscheme for hidden Markov models (HMM).A robust estimation scheme is first presented using the minimax method thatminimizes a worst case cost for HMMs with bounded uncertainties.Then we present a mixed estimation scheme that minimizes arisk-neutral cost with a constraint on the worst-case cost. Somesimulation results are also presented to compare these different estimationschemes in cases of uncertainties in the noise model.<P><Center><I>The research and scientific content in this material has been accepted for presentation in the 37th IEEE Conference on Decision and Control, Tampa, December 1998.</I></Center>en_US
dc.format.extent113802 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5950
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1998-31en_US
dc.subjectfilteringen_US
dc.subjectrobust controlen_US
dc.subjecthidden Markov modelsen_US
dc.subjectmixed estimationen_US
dc.subjectrisk-sensitive,en_US
dc.titleA Framework for Mixed Estimation of Hidden Markov Modelsen_US
dc.typeTechnical Reporten_US

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