• DocumentCode
    1243294
  • Title

    Enhanced-Convergence Normalized LMS Algorithm[DSP Tips & Tricks]

  • Author

    Givens, Maurice

  • Volume
    26
  • Issue
    3
  • fYear
    2009
  • fDate
    5/1/2009 12:00:00 AM
  • Firstpage
    81
  • Lastpage
    95
  • Abstract
    Least mean square (LMS) algorithms have found great utility in many adaptive filtering applications. This article shows how the traditional constraints placed on the update gain of normalized LMS algorithms are overly restrictive. We present relaxed update gain constraints that significantly improve normalized LMS algorithm convergence speed.
  • Keywords
    adaptive filters; least mean squares methods; adaptive filtering applications; enhanced-convergence normalized LMS algorithm; least mean square algorithms; Adaptive filters; Algorithm design and analysis; Convergence; Error correction; Filtering algorithms; Gain; Least squares approximation; Signal design; Signal processing algorithms; Upper bound;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2009.932168
  • Filename
    4815545
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1243294