Discrete Signal Reconstruction by Sum of Absolute Values

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Abstract

In this letter, we consider a problem of reconstructing an unknown discrete signal taking values in a finite alphabet from incomplete linear measurements. The difficulty of this problem is that the computational complexity of the reconstruction is exponential as it is. To overcome this difficulty, we extend the idea of compressed sensing, and propose to solve the problem by minimizing the sum of weighted absolute values. We assume that the probability distribution defined on an alphabet is known, and formulate the reconstruction problem as linear programming. Examples are shown to illustrate that the proposed method is effective.

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Details 詳細情報について

  • CRID
    1050564285766886016
  • NII Article ID
    120005619769
  • NII Book ID
    AA1099314X
  • ISSN
    10709908
  • HANDLE
    2433/198575
  • Text Lang
    en
  • Article Type
    journal article
  • Data Source
    • IRDB
    • CiNii Articles

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