• DocumentCode
    16216
  • Title

    A Necessary and Sufficient Condition for Generalized Demixing

  • Author

    Chun-Yen Kuo ; Gang-Xuan Lin ; Chun-Shien Lu

  • Author_Institution
    Inst. of Inf. Sci., Taipei, Taiwan
  • Volume
    22
  • Issue
    11
  • fYear
    2015
  • fDate
    Nov. 2015
  • Firstpage
    2049
  • Lastpage
    2053
  • Abstract
    Demixing is the problem of identifying multiple structured signals from a superimposed observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. We present a new solution to determine whether or not a specific convex optimization problem built for generalized demixing is successful. This solution also creates a way to estimate the probability of success by the approximate kinematic formula.
  • Keywords
    compressed sensing; convex programming; probability; signal denoising; approximate kinematic formula; compressive sensing; convex optimization problem; generalized demixing problem; multiple structured signal identification; probability; Compressed sensing; Convex functions; Economic indicators; Kinematics; Null space; Optimization; Standards; ${ell _1}$-minimization; Compressive sensing; conic geometry; convex optimization; sparse signal recovery;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2015.2457403
  • Filename
    7160687
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=16216