Classroom note: Building simple hidden Markov models

Wai Ki Ching; Michael K. Ng

doi:10.1080/00207390310001638386

Classroom note: Building simple hidden Markov models

Wai Ki Ching
, Michael K. Ng

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

3 Citations (Scopus)

Abstract

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Original language	English
Pages (from-to)	296-299
Number of pages	4
Journal	International Journal of Mathematical Education in Science and Technology
Volume	35
Issue number	2
DOIs	https://doi.org/10.1080/00207390310001638386
Publication status	Published - 1 Mar 2004

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SDG 9 Industry, Innovation, and Infrastructure

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10.1080/00207390310001638386

Cite this

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title = "Classroom note: Building simple hidden Markov models",

abstract = "Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.",

author = "Ching, \{Wai Ki\} and Ng, \{Michael K.\}",

note = "Research supported in part by RGC Grant No. HKU 7126/02P and HKU CRCG Grant Nos. 10203907, 10204437, 10203501, 10205105 and 10204436.",

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AU - Ng, Michael K.

N1 - Research supported in part by RGC Grant No. HKU 7126/02P and HKU CRCG Grant Nos. 10203907, 10204437, 10203501, 10205105 and 10204436.

PY - 2004/3/1

Y1 - 2004/3/1

N2 - Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

AB - Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

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JO - International Journal of Mathematical Education in Science and Technology

JF - International Journal of Mathematical Education in Science and Technology

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Classroom note: Building simple hidden Markov models

Abstract

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