• DocumentCode
    2140667
  • Title

    Optimal error for Orthogonal Matching Pursuit for μ-coherent dictionaries

  • Author

    Jingfan Long ; Xiujie Wei ; Peixin Ye

  • Author_Institution
    Beijing Inf. Sci. & Technol. Univ., Beijing, China
  • fYear
    2013
  • fDate
    23-25 July 2013
  • Firstpage
    1408
  • Lastpage
    1413
  • Abstract
    In this paper, we investigate the efficiency of some kind of Greedy Algorithms with respect to dictionaries from Hilbert spaces. We establish ideal Lebesgue-type inequality for Orthogonal Matching Pursuit which is also known as the Orthogonal Greedy Algorithm for μ-coherent dictionaries. We show that the Orthogonal Matching Pursuit provides an almost optimal approximation on the first [1/18μ] steps.
  • Keywords
    Hilbert spaces; approximation theory; error analysis; greedy algorithms; learning (artificial intelligence); μ-coherent dictionaries; Hilbert spaces; error analysis; ideal Lebesgue-type inequality; optimal approximation; optimal error; orthogonal greedy algorithm; orthogonal matching pursuit; Approximation methods; Coherence; Dictionaries; Educational institutions; Frequency modulation; Greedy algorithms; Matching pursuit algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2013 Ninth International Conference on
  • Conference_Location
    Shenyang
  • Type

    conf

  • DOI
    10.1109/ICNC.2013.6818200
  • Filename
    6818200