2026-08-11T05:57:03Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:13284 2024-03-06T10:52:01Z ddc:004 open_access

Equivalence of Hidden Markov Models with Continuous Observations Darwin, Oscar Kiefer, Stefan Markov chains equivalence probabilistic systems verification We consider Hidden Markov Models that emit sequences of observations that are drawn from continuous distributions. For example, such a model may emit a sequence of numbers, each of which is drawn from a uniform distribution, but the support of the uniform distribution depends on the state of the Hidden Markov Model. Such models generalise the more common version where each observation is drawn from a finite alphabet. We prove that one can determine in polynomial time whether two Hidden Markov Models with continuous observations are equivalent. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Oscar Darwin and Stefan Kiefer 2020 Is Part Of LIPIcs, Volume 182, 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.FSTTCS.2020.43 urn:nbn:de:0030-drops-132845 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2020.43 eng https://creativecommons.org/licenses/by/3.0/legalcode