2008, English, Article edition: Estimating the mixing matrix in Sparse Component Analysis (SCA) using EM algorithm and Iteratice bayesian clustering Zayyani, Hadi; Babaie-Zadeh, Massoud; Jutten, Christian

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Bookmark: http://trove.nla.gov.au/version/206497
Physical Description
  • text
Published
  • HAL - CCSD
  • 2008
Language
  • English

Edition details

Title
  • Estimating the mixing matrix in Sparse Component Analysis (SCA) using EM algorithm and Iteratice bayesian clustering
Author
  • Zayyani, Hadi
  • Babaie-Zadeh, Massoud
  • Jutten, Christian
Published
  • HAL - CCSD
  • 2008
Physical Description
  • text
Subjects
Notes
  • In this paper, we focus on the mixing matrix estimation which is the first step of Sparse Component Analysis. We propose a novel algorithm based on Expectation- Maximization (EM) algorithm in the case of two-sensor set up. Then, a novel iterative Bayesian clustering is applied to yield better results in estimating the mixing matrix. Also, we compute the Maximum Likelihood (ML) estimates of the elements of the second row of the mixing matrix based on each cluster. The simulations show that the proposed method has better accuracy and less failure than the EM-Laplacian Mixture Model (EM-LMM) method.
  • HAL:hal-00315889, version 1
  • HAL:http:/​/​hal.archives-ouvertes.fr/​hal-00315889/​en/​
Language
  • English
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