• DocumentCode
    2225474
  • Title

    Analytical model for the mean weights of two adaptive interpolated-FIR filter structures

  • Author

    Tobias, Orlando J. ; Seara, Rui ; da Rocha, Carlos A. F.

  • Author_Institution
    Dept. of Electr. Eng., Univ. Fed. de Santa Catarina, Florianopolis, Brazil
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    93
  • Abstract
    This paper presents an analytical model for the mean weight behavior of two AIFIR structures using the LMS algorithm to adapt the sparse filter weights. The introduction of an interpolating block cascaded with the adaptive sparse filter imposes signal correlations. On the other hand, it is well known that such correlations are disregarded by the independence theory, which is the base for the stochastic analysis of the LMS algorithm. The proposed models have been derived without using the independence theory. Simulation results demonstrate the effectiveness of the proposed analytical models as compared with the classical analysis
  • Keywords
    FIR filters; adaptive filters; digital filters; interpolation; least mean squares methods; sparse matrices; AIFIR; LMS algorithm; adaptive interpolated-FIR filter structures; analytical model; independence theory; interpolating block; mean weights; signal correlations; sparse filter weights; stochastic analysis; Adaptive filters; Algorithm design and analysis; Analytical models; Arithmetic; Finite impulse response filter; Instruments; Laboratories; Least squares approximation; Predictive models; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
  • Conference_Location
    Geneva
  • Print_ISBN
    0-7803-5482-6
  • Type

    conf

  • DOI
    10.1109/ISCAS.2000.856004
  • Filename
    856004