• DocumentCode
    1213518
  • Title

    Linear prediction of subband signals

  • Author

    Tan, Siew-Lian ; Fischer, Thomas R.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
  • Volume
    12
  • Issue
    9
  • fYear
    1994
  • fDate
    12/1/1994 12:00:00 AM
  • Firstpage
    1576
  • Lastpage
    1583
  • Abstract
    The performance of linear prediction of fullband and subband signals is described in terms of the respective prediction gain. The subband prediction gain is characterized in terms of the fullband signal power spectral density and the frequency response of the subband filters. For Gaussian fullband signals, the asymptotic subband prediction gain can never be larger than the asymptotic fullband prediction gain. Simulation results compare fixed and adaptive fullband and subband prediction gains for Gaussian sources and speech. For speech, the subband prediction gain can exceed the fullband prediction gain
  • Keywords
    Gaussian processes; filtering theory; frequency response; prediction theory; signal processing; speech coding; Gaussian fullband signals; Gaussian sources; asymptotic fullband prediction gain; asymptotic subband prediction gain; frequency response; fullband signals; linear prediction; performance; power spectral density; respective prediction gain; speech; subband signals; Discrete wavelet transforms; Filters; Frequency response; Helium; Image coding; Performance gain; Predictive models; Signal processing; Signal resolution; Speech;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/49.339926
  • Filename
    339926