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Learning Object: Hidden Markov Models

TitleHidden Markov Models
Authors
Contributors
Issue Date2004
DescriptionHidden Markov Models (HMMs) are widely used in science, engineering and many other areas. In a HMM, there are two types of states: the hidden states and the observable states. Here we present a HMM via the framework of classical Markov chain model. A simple estimation method for the transition probabilities among the hidden states is also discussed.
metadata.dc.description.urihttp://hkumath.hku.hk/~wkc/MathModel/index.php?area=method&topics=HMM
Persistent Identifierhttp://hdl.handle.net/10722/49903

 

DC FieldValueLanguage
dc.contributorThe University of Hong Kongen_HK
dc.contributor.authorChing, Wai Kien_HK
dc.date.accessioned2008-10-21T08:12:53Z-
dc.date.available2008-10-21T08:12:53Z-
dc.date.issued2004en_HK
dc.identifier.urihttp://hdl.handle.net/10722/49903-
dc.descriptionHidden Markov Models (HMMs) are widely used in science, engineering and many other areas. In a HMM, there are two types of states: the hidden states and the observable states. Here we present a HMM via the framework of classical Markov chain model. A simple estimation method for the transition probabilities among the hidden states is also discussed.en_HK
dc.description.urihttp://hkumath.hku.hk/~wkc/MathModel/index.php?area=method&topics=HMMen_HK
dc.languageengen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsThis work is licensed under the Creative Commons Attribution - NoDerivs - NonCommercial license. To view a copy of this license go to: < http://creativecommons.org/licenses/by-nc-nd/2.0/' target='new' >;visit http://creativecommons.org/licenses/by-nc-nd/2.0/,or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.en_HK
dc.titleHidden Markov Modelsen_HK
dc.typeLearning_Objecten_HK
dc.identifier.emailwkc@maths.hku.hken_HK
dc.identifier.email2859-2256en_HK
dc.description.naturepublished_or_final_versionen_HK

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