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Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions

contributor authorRamasso, Emmanuel
contributor authorDenoeux, Thierry
date accessioned2020-03-12T18:22:59Z
date available2020-03-12T18:22:59Z
date issued2014
identifier issn1063-6706
identifier other6507644.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/956609?show=full
formatgeneral
languageEnglish
publisherIEEE
titleMaking Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions
typeJournal Paper
contenttypeMetadata Only
identifier padid7988688
subject keywordsexpectation-maximisation algorithm
subject keywordshidden Markov models
subject keywordsmaximum likelihood estimation
subject keywordsparameter estimation
subject keywordsHMM
subject keywordsbelief function framework
subject keywordsbelief functions
subject keywordsexpectation-maximization algorithm
subject keywordshidden Markov models
subject keywordshidden states
subject keywordsmaximum likelihood estimation
subject keywordsparameter estimation
subject keywordspartial knowledge
subject keywordsstate prediction
subject keywordsDempster&
subject keywords#x2013
subject keywordsShafer theory
subject keywordsevidence theory
subject keywordsevidential expectation-maximization (E<
subject keywordsformula formulatype="
subject keywordsinline"
subject keywords>
subject keywords<
subject keywordstex Notation="
subject keywordsTeX"
subject keywords>
subject keywords$^2$
identifier doi10.1109/TFUZZ.2013.2259496
journal titleFuzzy Systems, IEEE Transactions on
journal volume22
journal issue2
filesize652337
citations0


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