• DocumentCode
    1743200
  • Title

    Convergence analysis of the variable weight mixed-norm LMS-LMF adaptive algorithm

  • Author

    Zerguine, Azzedine ; Aboulnasr, Tyseer

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • Volume
    1
  • fYear
    2000
  • fDate
    Oct. 29 2000-Nov. 1 2000
  • Firstpage
    279
  • Abstract
    In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. Sufficient and necessary conditions for the convergence of the algorithm are derived. Furthermore, bounds on the step size to ensure convergence of the LMF algorithm are also derived.
  • Keywords
    adaptive filters; convergence of numerical methods; filtering theory; least mean squares methods; minimisation; time-varying filters; convergence analysis; cost functions; objective function; step size; sufficient and necessary conditions; time varying weighting factor; variable weight mixed-norm LMS-LMF adaptive algorithm; weighted sum; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Computer errors; Convergence; Cost function; Equations; Least squares approximation; Minerals; Petroleum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-7803-6514-3
  • Type

    conf

  • DOI
    10.1109/ACSSC.2000.910959
  • Filename
    910959