Optimal filters for a hidden Markov random field model
type: Item
instance of: scholarly article
title: Optimal filters for a hidden Markov random field model
zbMATH Open document ID: 0957.93082
DOI: 10.1016/S0895-7177(00)00107-2
published in: Mathematical and Computer Modelling
publication date: 2000-11-14T00:00:00Z
review text: Markov random fields models are a convenient technical tool for modeling and studying numerous phenomena that occur in real life, in particular where one is interested in processes exhibiting some type of spatio-temporal variability. This paper presents optimal filters for the states of a partially observed temporal Markov random field. The parameter estimation problem is also discussed.
reviewed by: Vyacheslav A. Vasiliev
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 60G35
Mathematics Subject Classification ID: 60J05
zbMATH DE Number: 1529779
zbMATH Keywords: hidden Markov models
zbMATH Keywords: spatio-temporal models
zbMATH Keywords: optimal filtering
zbMATH Keywords: measure change techniques
author: Lakhdar Aggoun
author: Lakdere Benkherouf
author: Ali Benmerzouga
describes a project that uses: spatial
MaRDI profile type: Publication
cites work: M.A.P.Estimation for hidden discrete Markov random fields
cites work: Q3750011
cites work: Statistical Inference for Spatial Processes
cites work: On the stability of the geostatistical method
cites work: Q4323296
full work available at URL: s0895-7177(00)00107-2
OpenAlex ID: W2024548434
description: scientific article; zbMATH DE number 1529779