• DocumentCode
    350739
  • Title

    Adaptive IIR filtering for noisy input-output systems

  • Author

    Zheng, Wei Xing

  • Author_Institution
    Sch. of Sci., Univ. of Western Sydney, Kingswood, NSW, Australia
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    375
  • Abstract
    This paper is concerned with adaptive IIR filtering for linear systems with noisy input and output measurements. A new and numerically efficient procedure for estimating the variances of the white input and output noises is established so that the adaptive IIR filter based on the bias-eliminated least-squares algorithm can be efficiently implemented. This new adaptive IIR filter can achieve a substantial reduction in computational effort, and can retain almost the same parameter estimation accuracy. Numerical results that illustrate the attractive properties of the new adaptive FIR filter are presented
  • Keywords
    IIR filters; adaptive filters; filtering theory; least squares approximations; linear systems; parameter estimation; white noise; adaptive IIR filtering; bias-eliminated least-squares algorithm; linear systems; noisy input-output systems; numerical results; numerically efficient procedure; parameter estimation accuracy; variance estimation; white noise; Adaptive filters; Australia; Filtering; IIR filters; Nonlinear filters; Parameter estimation; Pollution measurement; Riccati equations; Signal processing; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on
  • Conference_Location
    Brisbane, Qld.
  • Print_ISBN
    1-86435-451-8
  • Type

    conf

  • DOI
    10.1109/ISSPA.1999.818190
  • Filename
    818190