A HIDDEN MARKOV MODEL: DEPENDENCIES BETWEEN RANDOM VARIABLES AND ITS REPRESENTATION | Zendy

B. SETIAWATY | Zendy

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A HIDDEN MARKOV MODEL: DEPENDENCIES BETWEEN RANDOM VARIABLES AND ITS REPRESENTATION

Author(s) -

B. SETIAWATY

Publication year - 2002

Publication title -

milang journal of mathematics and its applications

Language(s) - English

Resource type - Journals

ISSN - 2963-5233

DOI - 10.29244/jmap.1.2.11-22

Subject(s) - hidden markov model , hidden semi markov model , variable order markov model , representation (politics) , markov model , markov chain , computer science , set (abstract data type) , maximum entropy markov model , markov property , markov process , random variable , mathematics , theoretical computer science , artificial intelligence , machine learning , statistics , law , programming language , politics , political science

This article shows the nature of dependencies between random variables in a hidden Markov model. Using these properties,we will show that the law of a hidden Markov model is completely specied by a set of four parameters which is called a representation of the hidden Markov model.

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