• DocumentCode
    3158190
  • Title

    Generalized thresholding sparsity-aware algorithm for low complexity online learning

  • Author

    Kopsinis, Yannis ; Slavakis, Konstantinos ; Theodoridis, Sergios ; McLaughlin, Steve

  • Author_Institution
    Univ. of Granada, Granada, Spain
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    3277
  • Lastpage
    3280
  • Abstract
    In this paper, a novel scheme for online, sparsity-aware learning is presented. A new theory is developed that allows for the incorporation, in a unifying way, of different thresholding rules to promote sparsity, that may even be of a nonconvex nature. The complexity of the algorithm exhibits a linear dependence on the number of free parameters.
  • Keywords
    adaptive filters; learning (artificial intelligence); adaptive filtering; low complexity online learning; sparsity-aware algorithm; sparsity-aware learning; thresholding operator; Computational complexity; Convergence; Noise; Noise measurement; Training; Vectors; Adaptive filtering; signal recovery; sparsity; thresholding operators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288615
  • Filename
    6288615
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3158190