Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise

DOI10.1016/j.sigpro.2010.05.033zbMath1203.94037OpenAlexW2168062689MaRDI QIDQ612566

Jérôme Lapuyade-Lahorgue, Pierre Lanchantin, Wojciech Pieczynski

Publication date: 29 December 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2010.05.033

zbMATH Keywords

copulascorrelated noisetexture classificationimage segmentationnon-Gaussian noisestochastic EMhidden Markov chainsiterative conditional estimationnon-stationary data segmentationtriplet Markov chainsunsupervised signal segmentation

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

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A copula-based multivariate hidden Markov model for modelling momentum in football ⋮ Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data ⋮ Pairwise Markov models and hybrid segmentation approach ⋮ SVD-based state and parameter estimation approach for generalized Kalman filtering with application to GARCH-in-Mean estimation ⋮ Unsupervised data classification using pairwise Markov chains with automatic copulas selection ⋮ Existence of infinite Viterbi path for pairwise Markov models

Cites Work

• Unnamed Item
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• Nonstationary hidden Markov model
• An introduction to copulas.
• Unsupervised multiscale oil slick segmentation from SAR images using a vector HMC model
• Unsupervised segmentation of triplet Markov chains hidden with long-memory noise
• Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise
• Multisensor triplet Markov chains and theory of evidence
• Unsupervised signal restoration using hidden Markov chains with copulas
• Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem
• Fuzzy pairwise Markov chain to segment correlated noisy data
• Inference in hidden Markov models.
• On convergence of the iterative conditional estimations
• Gaussian copulas in triplet, partially Markov chains
• On Some Criteria for Estimating the Order of a Markov Chain
• Stochastic versions of the em algorithm: an experimental study in the mixture case
• Kalman Filtering in Triplet Markov Chains
• Hidden Markov processes
• Fuzzy Markovian Segmentation in Application of Magnetic Resonance Images
• Signal and Image Segmentation Using Pairwise Markov Chains
• Hidden Markov models for bioinformatics

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