Minimum mean square error quantizers with uncorrelated input and quantization noise

Author

Hjorungnes, A. ; Saramäki, Tapio

Author_Institution

Signal Process. Lab., Tampere Univ. of Technol., Finland

Volume

2

fYear

2001

fDate

6-9 May 2001

Firstpage

129

Abstract

Scalar quantizers with the minimum mean square error are designed in the case where the input signal and the quantization noise are uncorrelated. The probability density function (pdf) of the stochastic signal is assumed to be known. This design is then generalized to vector quantizers in the case where the expected value of the inner product between the input and quantization noise vector are equal to zero. The results show that the representation levels of the proposed quantizers are scaled versions of the representation levels of the well-known pdf optimized quantizers. The proposed quantizers are useful in subband coding applications

Keywords

mean square error methods; source coding; vector quantisation; inner product; input signal; minimum mean square error quantizers; probability density function; quantization noise; representation levels; scalar quantizers; stochastic signal; subband coding applications; uncorrelated input; vector quantizers; Additive noise; Biomedical signal processing; Filter bank; Finite impulse response filter; Mean square error methods; Noise figure; Probability density function; Quantization; Source coding; Stochastic resonance;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-6685-9

Type

conf

DOI

10.1109/ISCAS.2001.921023

Filename

921023