• DocumentCode
    302608
  • Title

    Optimum pre- and postfilters for quantization

  • Author

    Tuqan, Jamal ; Vaidyanathan, P.P.

  • Author_Institution
    Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA
  • Volume
    2
  • fYear
    1996
  • fDate
    12-15 May 1996
  • Firstpage
    461
  • Abstract
    We consider the optimization of pre- and post filters surrounding a uniform quantizer such that the mean square error due to quantization is minimized. Unlike some previous work, the postfilter is not restricted to be the inverse of the prefilter. With no order constraint on the filters, we present closed form solutions for the optimum pre- and post filters. Using these optimum solutions, we obtain a coding gain expression for the system under study. We then repeat the same analysis with first order pre- and post filters in the form 1+αz-1 and 1/(1+γz-1) providing some examples where we compare coding gain performance with the case of α=γ
  • Keywords
    FIR filters; IIR filters; filtering theory; optimisation; quantisation (signal); closed form solutions; coding gain performance; mean square error; optimization; optimum postfilter; optimum prefilter; uniform quantizer; Channel bank filters; Closed-form solution; Filter bank; Mean square error methods; Performance analysis; Performance gain; Quantization; Random processes; White noise; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-3073-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1996.541746
  • Filename
    541746