Identifying combinatorially symmetric Hidden Markov Models

  title={Identifying combinatorially symmetric Hidden Markov Models},
  author={Daniel Burgarth},
  journal={arXiv: Combinatorics},
  • D. Burgarth
  • Published 9 September 2017
  • Mathematics
  • arXiv: Combinatorics
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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