Identifying combinatorially symmetric Hidden Markov Models

Abstract

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.

Although the result is very simple, I could not find much (closely) related work. If I missed out something I'd be grateful if you could let me know via email to [email protected]