• DocumentCode
    894444
  • Title

    A frequency domain model for `filtered´ LMS algorithms-stability analysis, design, and elimination of the training mode

  • Author

    Feintuch, Paul L. ; Bershad, Neil J. ; Lo, Allen K.

  • Author_Institution
    Hughes Aircraft Co., Fullerton, CA, USA
  • Volume
    41
  • Issue
    4
  • fYear
    1993
  • fDate
    4/1/1993 12:00:00 AM
  • Firstpage
    1518
  • Lastpage
    1531
  • Abstract
    A frequency domain model of the filtered LMS algorithm is presented for analyzing the behavior of the weights during adaptation. In particular, expressions for stable operation of the algorithm are derived as a function of the algorithm step size, the input signal power, and the transfer functions of the linear filters. The expressions show that algorithm stability can be achieved over a frequency band of interest by inserting an appropriately chosen delay in the reference input to the LMS algorithm weight update equation. This result implies that it is not necessary to use a training mode to estimate the loop transfer functions before or during adaptation if the input is limited to a band of frequencies. It is only necessary to know the approximate delay introduced by the transfer functions in the band. The single delay parameter can be estimated much more easily than the entire transfer function. Simulations of the time domain algorithm are presented to support the theoretical predictions of the frequency domain model
  • Keywords
    acoustic noise; acoustic signal processing; adaptive filters; frequency-domain analysis; least squares approximations; noise abatement; stability; transfer functions; active acoustic noise canceller; delay parameter; design; filtered LMS algorithms; frequency domain model; stability analysis; training mode elimination; transfer functions; weights; Algorithm design and analysis; Delay estimation; Equations; Frequency domain analysis; Frequency estimation; Least squares approximation; Nonlinear filters; Predictive models; Stability; Transfer functions;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.212728
  • Filename
    212728