A variational Bayesian approach to number of sources estimation for multichannel blind deconvolution

DOI10.1007/s11760-007-0040-5zbMath1255.68176OpenAlexW2159928843MaRDI QIDQ1934500

Liangsuo Ma, Ah Chung Tsoi

Publication date: 29 January 2013

Published in: Signal, Image and Video Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11760-007-0040-5

zbMATH Keywords

independent component analysismodel order selectionvariational Bayesensemble learningmultichannel blind deconvolution

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Machine vision and scene understanding (68T45)

Uses Software

• ICALAB

Cites Work

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• Choice of basis for Laplace approximation
• An introduction to variational methods for graphical models
• A unified balanced approach to multichannel blind deconvolution
• Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG
• Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks