A variational Bayesian methodology for hidden Markov models utilizing Student's-\(t\) mixtures

DOI10.1016/j.patcog.2010.09.001zbMath1211.68349OpenAlexW2100807019WikidataQ56115038 ScholiaQ56115038MaRDI QIDQ614085

Sotirios P. Chatzis, Dimitrios I. Kosmopoulos

Publication date: 23 December 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.09.001

zbMATH Keywords

hidden Markov modelsvariational BayesStudent's \(t\)-distributionspeaker identificationrobotic task failureviolence detection

Mathematics Subject Classification ID

Bayesian inference (62F15) Pattern recognition, speech recognition (68T10) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (7)

A Novel Continuous Hidden Markov Model for Modeling Positive Sequential Data ⋮ Shifted-Scaled Dirichlet-Based Hierarchical Dirichlet Process Hidden Markov Models with Variational Inference Learning ⋮ Identification of jump Markov autoregressive exogenous systems with missing measurements ⋮ A Markov-switching regression model with non-Gaussian innovations: estimation and testing ⋮ A reservoir-driven non-stationary hidden Markov model ⋮ Robust identification of linear ARX models with recursive EM algorithm based on Student's t-distribution ⋮ Online identification of time‐delay jump Markov autoregressive exogenous systems with recursive expectation‐maximization algorithm

Uses Software

• UCI-ml
• PRMLT

Cites Work

• Robust Bayesian clustering
• Singularities in mixture models and upper bounds of stochastic complexity.
• Inference in hidden Markov models.
• Signal Modeling and Classification Using a Robust Latent Space Model Based on $t$ Distributions
• Variational Bayes for generalized autoregressive models
• Mixture-based extension of the AR model and its recursive Bayesian identification
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