• DocumentCode
    2827848
  • Title

    Preconditioned conjugate gradient methods for adaptive filtering

  • Author

    Hull, Andrew W. ; Jenkins, W. Kenneth

  • Author_Institution
    Illinois Univ., Urbana, IL, USA
  • fYear
    1991
  • fDate
    11-14 Jun 1991
  • Firstpage
    540
  • Abstract
    The method of preconditioned conjugate gradients (PCGs) is proposed for solving the problem of adaptive filtering. Considered as an iterative algorithm, the PCG algorithm is asymptotically efficient. It is suggested for use in applications requiring very high order adaptive filters. The method is also extended to the IIR (infinite impulse response) case. Application to the PCG algorithm to very long filters is suggested to exploit the fact that the number of iterations of the PCG algorithm until convergence is independent of the filter order. In a block algorithm, then, increasing filter length increases the efficiency of the algorithm
  • Keywords
    adaptive filters; digital filters; filtering and prediction theory; adaptive filtering; asymptotically efficient; filter length; filter order; high order adaptive filters; iterative algorithm; long filters; preconditioned conjugate gradient methods; Adaptive algorithm; Adaptive filters; Application software; Character generation; Computational complexity; Convergence; Costs; Gradient methods; Iterative algorithms; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1991., IEEE International Sympoisum on
  • Print_ISBN
    0-7803-0050-5
  • Type

    conf

  • DOI
    10.1109/ISCAS.1991.176392
  • Filename
    176392