Forgetting of the initial distribution for non-ergodic Hidden Markov Chains
| dc.creator | Gassiat, Elisabeth | |
| dc.creator | Landelle, Benoit | |
| dc.creator | Moulines, Eric | |
| dc.date | 2008-10-12 | |
| dc.date.accessioned | 2026-07-07T10:09:32Z | |
| dc.date.available | 2026-07-07T10:09:32Z | |
| dc.description | In this paper, the forgetting of the initial distribution for a non-ergodic Hidden Markov Models (HMM) is studied. A new set of conditions is proposed to establish the forgetting property of the filter, which significantly extends all the existing results. Both a pathwise-type convergence of the total variation distance of the filter started from two different initial distributions, and a convergence in expectation are considered. The results are illustrated using generic models of non-ergodic HMM and extend all the results known so far. | |
| dc.description | 31 pages | |
| dc.identifier | https://arxiv.org/abs/0810.2123 | |
| dc.identifier | http://arxiv.org/abs/0810.2123 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/171348 | |
| dc.subject | Probability | |
| dc.subject | 93E11,60G35 | |
| dc.title | Forgetting of the initial distribution for non-ergodic Hidden Markov Chains | |
| dc.type | text |