• DocumentCode
    1917860
  • Title

    Sparse Binary Matrices of LDPC Codes for Compressed Sensing

  • Author

    Lu, Weizhi ; Kpalma, Kidiyo ; Ronsin, Joseph

  • Author_Institution
    IETR, Univ. Eur. de Bretagne, Rennes, France
  • fYear
    2012
  • fDate
    10-12 April 2012
  • Firstpage
    405
  • Lastpage
    405
  • Abstract
    We present the sparse binary matrix defined by low-density parity-check (LDPC) codes as measurement matrix in compressed sensing. This kind of matrix owns much stronger orthogonality than current other main measurement matrices. In practice, for a matrix given size, the optimal column degree for high orthogonality can also be determined by progressive edge-growth (PEG) algorithm.
  • Keywords
    parity check codes; signal reconstruction; sparse matrices; LDPC codes; PEG algorithm; compressed sensing; low-density parity-check codes; optimal column degree; progressive edge-growth algorithm; sparse binary matrices; Compressed sensing; Correlation; Current measurement; Loss measurement; Parity check codes; Signal processing algorithms; Sparse matrices; LDPC codes; compressed sensing; sparse binary matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference (DCC), 2012
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    978-1-4673-0715-4
  • Type

    conf

  • DOI
    10.1109/DCC.2012.60
  • Filename
    6189286
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1917860