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A null space method for over-complete blind source separation

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Publication:1020646
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DOI10.1016/j.csda.2007.03.009zbMath1445.62323OpenAlexW2143094923MaRDI QIDQ1020646

Ying Nian Wu, Ray-Bing Chen

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.03.009


zbMATH Keywords

singular value decompositionindependent component analysisMarkov chain Monte CarloGivens rotationBayesian latent variable modelLangevin-Euler equation


Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Bayesian inference (62F15) Applications of statistics (62P99) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)


Related Items

COPICA -- independent component analysis via copula techniques



Cites Work

  • Unnamed Item
  • Independent component analysis, a new concept?
  • Bayes inference in regression models with ARMA\((p,q)\) errors
  • A Variational Method for Learning Sparse and Overcomplete Representations
  • The Calculation of Posterior Distributions by Data Augmentation
  • Optimal Scaling of Discrete Approximations to Langevin Diffusions
  • Markovian source separation
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