• DocumentCode
    110401
  • Title

    Constructing Test Instances for Basis Pursuit Denoising

  • Author

    Lorenz, Dirk A.

  • Author_Institution
    Inst. for Anal. & Algebra, Tech. Univ. Braunschweig, Braunschweig, Germany
  • Volume
    61
  • Issue
    5
  • fYear
    2013
  • fDate
    1-Mar-13
  • Firstpage
    1210
  • Lastpage
    1214
  • Abstract
    The number of available algorithms for the so-called Basis Pursuit Denoising problem (or the related LASSO-problem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algorithms on different instances is growing. In this correspondence, we present a method to produce instances with exact solutions that is based on a simple observation, related to the so-called source condition from sparse regularization.
  • Keywords
    signal denoising; signal reconstruction; LASSO-problem; basis pursuit denoising problem; source condition; sparse regularization; Dynamic range; Inverse problems; Minimization; Noise; Noise reduction; Sparse matrices; Vectors; Basis Pursuit denoising; compressed sensing; optimization; optimization algorithms; signal processing algorithms; sparsity;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2012.2236322
  • Filename
    6399612