• DocumentCode
    2133262
  • Title

    Application of subband analysis to adaptive prediction

  • Author

    Saffle, James R. ; Rao, S.S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Villanova Univ., PA, USA
  • Volume
    3
  • fYear
    1998
  • fDate
    12-15 May 1998
  • Firstpage
    1725
  • Abstract
    A closed-loop adaptive subband prediction architecture is presented by employing an adaptive subband filter in the prediction configuration. Some authors have suggested that applying open-loop prediction methods to subband signals can realize increased prediction gain over fullband prediction. Furthermore, the benefits of applying multirate techniques to adaptive filtering are well understood in terms of reduction of computational complexity and increased convergence speed. Thus, the closed-loop subband adaptive predictor is a novel approach that is expected to exhibit these same benefits along with the advantages of backward adaptation. Results show that the new subband predictor can produce a higher prediction gain than a similar fullband adaptive prediction filter. The proposed architecture is implemented in C++ on the Pentium processor
  • Keywords
    adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; digital filters; filtering theory; least mean squares methods; prediction theory; C++; Pentium processor; adaptive prediction; adaptive subband filter; backward adaptation; closed-loop adaptive subband prediction architecture; computational complexity reduction; convergence speed; fullband prediction; multirate techniques; prediction gain; subband analysis; subband signals; Adaptive filters; Application software; Computational complexity; Computer architecture; Convergence; Delay; Prediction methods; Predictive models; Spectral analysis; Speech coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-4428-6
  • Type

    conf

  • DOI
    10.1109/ICASSP.1998.681791
  • Filename
    681791