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Identifying combinatorially symmetric Hidden Markov Models
Daniel Klaus Burgarth · 2017-09-09 · via math.ST updates on arXiv.org

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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