Message-passing algorithms for compressed sensing

  title={Message-passing algorithms for compressed sensing},
  author={David L. Donohoa and Arian Malekib and Andrea Montanaria},
  • David L. Donohoa, Arian Malekib, Andrea Montanaria
  • Published 2009
Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a known basis. Currently, the best known sparsity–undersampling tradeoff is achieved when reconstructing by convex optimization, which is expensive in important large-scale applications. Fast iterative thresholding algorithms have been intensively studied as… CONTINUE READING
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