Identifying combinatorially symmetric Hidden Markov Models

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3 Citations (SciVal)

Abstract

A sufficient criterion for the unique parameter identification of combinatorially symmetric Hidden Markov Models, based on the structure of their transition matrix, is provided. If the observed states of the chain form a zero forcing set of the graph of the Markov model, then it is uniquely identifiable and an explicit reconstruction method is given.
Original languageEnglish
Article number30
Pages (from-to)393-398
Number of pages6
JournalElectronic Journal of Linear Algebra
Volume34
Issue number1
DOIs
Publication statusPublished - Aug 2018

Keywords

  • Markov chains
  • Parameter identification
  • Zero forcing

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