Distributed variational Bayesian algorithms for Gaussian mixtures in sensor networks

DOI10.1016/j.sigpro.2009.10.004zbMath1197.94119OpenAlexW2052456085MaRDI QIDQ1957240

Mohammad Bagher Menhaj, B. Safarinejadian, Mehdi Karrari

Publication date: 24 September 2010

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

Full work available at URL: https://doi.org/10.1016/j.sigpro.2009.10.004

zbMATH Keywords

clusteringdensity estimationsensor networksmixture of Gaussiansvariational approximations

Mathematics Subject Classification ID

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

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New estimation in mixture of experts models using the Pearson type VII distribution ⋮ Distributed density estimation in sensor networks based on variational approximations ⋮ Variable selection in finite mixture of regression models using the skew-normal distribution

Cites Work

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• Variational approximations in Bayesian model selection for finite mixture distributions
• Convergence properties of a general algorithm for calculating variational Bayesian estimates for a normal mixture model