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Learning Object: Hidden Markov Models

TitleHidden Markov Models
Authors
Ching, Wai Ki
Contributors
The University of Hong Kong
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.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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