On Triplet Markov Chains
نویسندگان
چکیده
The restoration of a hidden process X from an observed process Y is often performed in the framework of hidden Markov chains (HMC). HMC have been recently generalized to triplet Markov chains (TMC). In the TMC model one introduces a third random chain U and assumes that the triplet T = (X,U, Y ) is a Markov chain (MC). TMC generalize HMC but still enable the development of efficient Bayesian algorithms for restoring X from Y . This paper lists some recent results concerning TMC; in particular, we recall how TMC can be used to model hidden semi-Markov Chains or deal with non-stationary HMC.
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