• DocumentCode
    2042049
  • Title

    The leaky least mean mixed norm algorithm

  • Author

    Nasar, Mohammed Abdul ; Zerguine, Azzedine

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • fYear
    2013
  • fDate
    3-6 Nov. 2013
  • Firstpage
    1520
  • Lastpage
    1523
  • Abstract
    In this work, a leakage-based variant of the Least Mean Mixed Norm (LMMN) algorithm, the leaky Least Mean Mixed Norm (LLMMN) algorithm, is derived. The proposed algorithm will help mitigate the weight drift problem experienced in the conventional Least Mean Square (LMS) and Least Mean Fourth (LMF) algorithms. The main aim of this work is to derive the LLMMN adaptive algorithm and conduct transient analysis using the energy conservation relation framework. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and show improved performance obtained through the use of LLMMN over the conventional LMMN algorithm in a weight drift environment.
  • Keywords
    adaptive filters; least mean squares methods; transient analysis; LLMMN adaptive algorithm; LMF algorithms; LMS algorithms; energy conservation relation framework; leakage-based variant; leaky least mean mixed norm algorithm; least mean fourth algorithms; least mean square algorithms; transient analysis; weight drift problem; Algorithm design and analysis; Convergence; Least squares approximations; Noise; Stability analysis; Transient analysis; Vectors; Adaptive filters; leaky least mean mixed norm; weight drift;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2013 Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • Print_ISBN
    978-1-4799-2388-5
  • Type

    conf

  • DOI
    10.1109/ACSSC.2013.6810550
  • Filename
    6810550