2007, English, Article edition: Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm Zayyani, Hadi; Babaie-Zadeh, Massoud; Mohimani, G. Hosein; ...

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Bookmark: http://trove.nla.gov.au/version/206616
Physical Description
  • text
Published
  • HAL - CCSD
  • 2007
Language
  • English

Edition details

Title
  • Sparse Component Analysis in Presence of Noise Using an Iterative EM-MAP Algorithm
Author
  • Zayyani, Hadi
  • Babaie-Zadeh, Massoud
  • Mohimani, G. Hosein
  • Jutten, Christian
Published
  • HAL - CCSD
  • 2007
Physical Description
  • text
Subjects
Notes
  • In this paper, a new algorithm for source recovery in under-determined Sparse Component Analysis (SCA) or atomic decomposition on over-complete dictionaries is presented in the noisy case. The algorithm is essentially a method for obtaining sufficiently sparse solutions of under-determined systems of linear equations with additive Gaussian noise. The method is based on iterative Expectation-Maximization of a Maximum A Posteriori estimation of sources (EM-MAP) and a new steepest-descent method is introduced for the optimization in the M-step. The solution obtained by the proposed algorithm is compared to the minimum L1-norm solution achieved by Linear Programming (LP). It is experimentally shown that the proposed algorithm is about one order of magnitude faster than the interior-point LP method, while providing better accuracy.
  • HAL:hal-00173379, version 1
  • HAL:http:/​/​hal.archives-ouvertes.fr/​hal-00173379/​en/​
Language
  • English
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