• DocumentCode
    3567176
  • Title

    New insights for the filtered-X algorithm and robust adaptive equalization

  • Author

    Hu, J. ; Wu, H.R.

  • Author_Institution
    Dept. of Comput. Syst. Eng., RMIT Univ., Melbourne, Vic., Australia
  • Volume
    1
  • fYear
    1999
  • Firstpage
    544
  • Abstract
    The filtered-X LMS algorithm is the most popular method for adaptive filter design in the field of active acoustic and vibration control because of its simplicity and good robust performance. However, no investigation has been conducted on whether the filtered-X LMS algorithm has generic advantages over that of the conventional LMS algorithm in terms of their different structures. In this paper, a heuristic explanation is provided to show that, under certain conditions, the additional filter in the filtered-X LMS algorithm can increase the system´s damping and move the closed-loop poles into deeper left halfplane, and hence increases the robust stability margin. In the illustrative example of a disturbed communication channel, Mont Carlo simulation results demonstrate that the filtered-X has a better robust performance than that of the conventional LMS.
  • Keywords
    Monte Carlo methods; adaptive equalisers; adaptive filters; least mean squares methods; telecommunication channels; Mont Carlo simulation; adaptive filter design; closed-loop poles; damping; disturbed communication channel; filtered-X LMS algorithm; filtered-X algorithm; robust adaptive equalization; robust stability margin; Adaptive equalizers; Adaptive filters; Adaptive systems; Communication channels; Filtering algorithms; Least squares approximation; Noise robustness; Performance analysis; Time varying systems; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
  • ISSN
    1058-6393
  • Print_ISBN
    0-7803-5700-0
  • Type

    conf

  • DOI
    10.1109/ACSSC.1999.832389
  • Filename
    832389