• DocumentCode
    1451075
  • Title

    Fast-convergence filtered regressor algorithms for blind equalisation

  • Author

    Douglas, S.C. ; Cichocki, Andrzej ; Amari, S.

  • Author_Institution
    Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA
  • Volume
    32
  • Issue
    23
  • fYear
    1996
  • fDate
    11/7/1996 12:00:00 AM
  • Firstpage
    2114
  • Lastpage
    2115
  • Abstract
    The authors present a simple extension of the standard Bussgang blind equalisation algorithms that significantly improves their convergence properties. The technique uses the inverse channel estimate to filter the regressor signal. The modified algorithms provide quasi-Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational complexity of the system. An example of the technique as applied to the constant-modulus algorithm indicates its superior convergence behaviour
  • Keywords
    computational complexity; convergence of numerical methods; deconvolution; equalisers; filtering theory; signal processing; blind equalisation; computational complexity; constant-modulus algorithm; convergence properties; cost function; fast-convergence algorithms; filtered regressor algorithms; inverse channel estimate; local minimum; quasi-Newton convergence;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19961414
  • Filename
    543782