• DocumentCode
    2867413
  • Title

    Adaptive recursive order statistic filters

  • Author

    Palmieri, Francesco

  • Author_Institution
    Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA
  • fYear
    1990
  • fDate
    3-6 Apr 1990
  • Firstpage
    1229
  • Abstract
    The ideas embodied by the recursive median filter are merged into a more general class of recursive LI-filters which includes both the infinite impulse response (IIR) filters and all the order statistic filters. The recursive LI-filter is a special case of a state-dependent system, and it can be seen as a more general IIR filter whose coefficients are picked up at every time step from a fixed set according to the order relationships existing among the elements of the observed window. An algorithm for adaptive computation of the coefficients of the recursive order statistic filters is derived. The algorithm is a steepest-descent search which follows an approach similar to that of the output-error formulation used in adaptive IIR filters. As a verification of convergence an example is shown in which the adaptive algorithm identifies successfully a recursive median filter and a recursive LI-filter. An example that shows how the recursive generalized filter has improved characteristics with respect to transient instabilities is also shown
  • Keywords
    adaptive filters; convergence; digital filters; filtering and prediction theory; spectral analysis; adaptive IIR filters; adaptive algorithm; convergence; recursive LI-filters; recursive median filter; recursive order statistic filters; Adaptive algorithm; Adaptive filters; Computational modeling; Convergence; Digital filters; IIR filters; Least squares approximation; Nonlinear filters; Resonance light scattering; Statistics; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
  • Conference_Location
    Albuquerque, NM
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.1990.115594
  • Filename
    115594