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Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 7 | Page No.: 1409-1414
DOI: 10.3923/itj.2011.1409.1414
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Iterative Weighted Gradient Projection for Sparse Reconstruction

Jun Deng, Guanghui Ren, Yansheng Jin and Wenjing Ning

Finding sparse solution to undetermined linear systems is one of the fundamental challenging issues in compressive sensing problems and other signal processing applications. This study has presented a novel iterative weighted gradient projection algorithm, referred to as the IWGP, to recover sparse signal in large-scale settings. IWGP is based on a widely used weighted filter technique in signal processing which reduces undesirable influence so that gradient projection can be applied to achieve computational efficiency. Numerical experiments are carried out and the results demonstrate the proposed algorithm is significantly faster than the fastest known methods for the l1 minimization programs and further show that the computational time isn’t sensitive to the sparsity level of original signal.
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How to cite this article:

Jun Deng, Guanghui Ren, Yansheng Jin and Wenjing Ning, 2011. Iterative Weighted Gradient Projection for Sparse Reconstruction. Information Technology Journal, 10: 1409-1414.

DOI: 10.3923/itj.2011.1409.1414






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