• DocumentCode
    754597
  • Title

    Recovery of short, complex linear combinations via ℓ1 minimization

  • Author

    Tropp, Joel A.

  • Author_Institution
    ICES, Univ. of Texas, Austin, TX
  • Volume
    51
  • Issue
    4
  • fYear
    2005
  • fDate
    4/1/2005 12:00:00 AM
  • Firstpage
    1568
  • Lastpage
    1570
  • Abstract
    This note provides a condition under which lscr1 minimization (also known as basis pursuit) can recover short linear combinations of complex vectors chosen from fixed, overcomplete collection. This condition has already been established in the real setting by Fuchs, who used convex analysis. The proof given here is more direct
  • Keywords
    Hilbert spaces; convex programming; linear programming; minimisation; sparse matrices; convex analysis; l1 minimization; linear combination; Atomic measurements; Dictionaries; Hilbert space; Ice; Linear approximation; Mathematical programming; Minimization methods; Signal synthesis; Software standards; Vectors; Algorithms; approximation; basis pursuit; linear program; redundant dictionaries; sparse representations;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2005.844057
  • Filename
    1412049
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=754597