• DocumentCode
    786758
  • Title

    A new adaptive algorithm to reduce weight fluctuations caused by high variance data

  • Author

    Cilke, J. Thomas ; Etter, Delores M.

  • Author_Institution
    Houston Tracker Syst., Englewood, CO, USA
  • Volume
    40
  • Issue
    9
  • fYear
    1992
  • fDate
    9/1/1992 12:00:00 AM
  • Firstpage
    2324
  • Lastpage
    2327
  • Abstract
    A nongradient iterative algorithm that has reduced adaptive filter weight fluctuations caused by high variance input data is presented. The algorithm adapts a single weight at each time step and has approximately the same computational requirements as the LMS algorithm
  • Keywords
    adaptive filters; filtering and prediction theory; iterative methods; adaptive algorithm; computational requirements; high variance input data; iterative methods; nongradient iterative algorithm; reduced adaptive filter weight fluctuations; time step; Adaptive algorithm; Adaptive filters; Convergence; Equations; Finite impulse response filter; Fluctuations; Gaussian processes; Noise cancellation; Predictive models; Signal processing algorithms;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.157274
  • Filename
    157274
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=786758