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
Link To Document :
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