文章基本信息

标题：Hidden Markov chains and fields with observations in Riemannian manifolds
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作者：Salem Said ; Nicolas Le Bihan ; Jonathan H. Manton 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：9
页码：719-724
DOI：10.1016/j.ifacol.2021.06.135
语种：English
出版社：Elsevier
摘要：AbstractHidden Markov chain, or Markov field, models, with observations in a Euclidean space, play a major role across signal and image processing. The present work provides a statistical framework which can be used to extend these models, along with related, popular algorithms (such as the Baum-Welch algorithm), to the case where the observations lie in a Riemannian manifold. It is motivated by the potential use of hidden Markov chains and fields, with observations in Riemannian manifolds, as models for complex signals and images.
关键词：KeywordsRiemannian manifoldhidden Markov modelMarkov fieldEM algorithm