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Source estimation in noisy sparse component analysis

Zayyani, H ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1109/ICDSP.2007.4288558
  3. Publisher: 2007
  4. Abstract:
  5. In this paper, a new algorithm for Sparse Component Analysis (SCA) in the noisy underdetermined case (i.e., with more sources than sensors) is presented. The solution obtained by the proposed algorithm is compared to the minimum l1 -norm solution achieved by Linear Programming (LP). Simulation results show that the proposed algorithm is approximately 10 dB better than the LP method with respect to the quality of the estimated sources. It is due to optimality of our solution (in the MAP sense) for source recovery in noisy underdetermined sparse component analysis in the case of spiky model for sparse sources and Gaussian noise. © 2007 IEEE
  6. Keywords:
  7. Boolean functions ; Digital signal processors ; Signal processing ; Digital signals ; International conferences ; New algorithm ; Source estimation ; Sparse component analysis (SCA) ; Digital signal processing
  8. Source: 2007 15th International Conference onDigital Signal Processing, DSP 2007, Wales, 1 July 2007 through 4 July 2007 ; July , 2007 , Pages 219-222 ; 1424408822 (ISBN); 9781424408825 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4288558