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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/28953
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dc.contributor.authorElliott, R.-
dc.contributor.authorMalcolm, W.-
dc.contributor.editorTheodore Djaferis,-
dc.date.issued2001-
dc.identifier.citationProceedings of the 40th IEEE Conference on Decision and Control : December 4-7, 2001, Hyatt Regency Grand Cypress, Orlando, Florida, USA / pp. 1-6 [CDROM]-
dc.identifier.urihttp://hdl.handle.net/2440/28953-
dc.description© Copyright 2001 IEEE-
dc.description.abstractIn this article, we consider hidden Markov model (HMM) parameter estimation in the context of an expectation maximisation (EM) algorithm. The models we study are discrete-time Markov chains observed in Gaussian noise. New formulae for updating smoothed estimates are given for the models just described.-
dc.description.statementofresponsibilityElliott, R.J. ; Malcolm, W.P.-
dc.language.isoen-
dc.publisherIEEE Systems Control Society-
dc.source.urihttp://dx.doi.org/10.1109/.2001.980402-
dc.titleImproved smoother dynamics for discrete time HMM parameter estimation-
dc.typeConference paper-
dc.contributor.conferenceIEEE Conference on Decision and Control (40th : 2001 : Orlando, Florida)-
dc.identifier.doi10.1109/.2001.980402-
dc.publisher.placeCDROM-
pubs.publication-statusPublished-
Appears in Collections:Applied Mathematics publications
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