Abstract
Hidden Markov Chains (HMC), Pairwise Markov Chains (PMC), and Triplet Markov Chains (TMC), allow one to estimate a hidden process X from an observed process Y. More recently, TMC have been generalized to Triplet Partially Markov chain (TPMC), where the estimation of X from Y remains workable. Otherwise, when introducing a Dempster-Shafer mass function instead of prior Markov distribution in classical HMC, the result of its Dempster-Shafer fusion with a distribution provided Y = y, which generalizes the posterior distribution of X, is a TMC. The aim of this Note is to generalize the latter result replacing HMC with multisensor TPMC.
| Translated title of the contribution | Fusion de Dempster-Shafer dans les chaînes triplet partiellement de Markov |
|---|---|
| Original language | English |
| Pages (from-to) | 797-802 |
| Number of pages | 6 |
| Journal | Comptes Rendus Mathematique |
| Volume | 339 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 1 Dec 2004 |