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Communication Dans Un Congrès Année : 2005

On Triplet Markov Chains

Résumé

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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Dates et versions

hal-04415484 , version 1 (24-01-2024)

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  • HAL Id : hal-04415484 , version 1

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Wojciech Pieczynski, François Desbouvries. On Triplet Markov Chains. ASMDA, May 2005, Brest, France. ⟨hal-04415484⟩
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