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Identifying combinatorially symmetric Hidden Markov Models

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 نشر من قبل Daniel Burgarth
 تاريخ النشر 2017
  مجال البحث
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We provide a sufficient criterion for the unique parameter identification of combinatorially symmetric Hidden Markov Models based on the structure of their transition matrix. 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.



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