• DocumentCode
    3773584
  • Title

    Modified Reduced Look Ahead Orthogonal Matching Pursuit under the Condition of Unknown Sparsity

  • Author

    Guan Chenhe

  • Author_Institution
    Sch. of Electron. Inf. &
  • Volume
    2
  • fYear
    2015
  • Firstpage
    79
  • Lastpage
    82
  • Abstract
    This paper introduces the basic information about compressive sensing theory and some reconstruction algorithms, such as Orthogonal Matching Pursuit (OMP) and Reduced Look Ahead Orthogonal Matching Pursuit (RLAOMP). RLAOMP performs well in reconstruction, but it needs the exact sparsity. We introduces a modified sparsity adaptive version of RLAOMP, which uses a Modified Sparsity Adaptive Matching Pursuit instead of the Subspace Pursuit to estimate the sparsity. The simulation results showed that it performs well under the condition of unknown sparsity.
  • Keywords
    "Matching pursuit algorithms","Sensors","Estimation","Reconstruction algorithms","Compressed sensing","Sparse matrices","Atomic measurements"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2015 8th International Symposium on
  • Print_ISBN
    978-1-4673-9586-1
  • Type

    conf

  • DOI
    10.1109/ISCID.2015.161
  • Filename
    7469085