Rates of convergence in adaptive universal vector quantization

Author

Effros, M. ; Chou, P.A. ; Gray, R.M.

Author_Institution

Inf. Syst. Lab., Stanford Univ., CA, USA

fYear

1994

fDate

27 Jun-1 Jul 1994

Firstpage

456

Abstract

We consider the problem of adaptive universal quantization. By adaptive quantization we mean quantization for which the delay associated with encoding the jth sample in a sequence of length n is bounded for all n>j. We demonstrate the existence of an adaptive universal quantization algorithm for which any weighted sum of the rate and the expected mean square error converges almost surely and in expectation as O(√(log log n/log n)) to the corresponding weighted sum of the rate and the distortion-rate function at that rate

Keywords

adaptive signal processing; coding errors; convergence of numerical methods; delays; error statistics; rate distortion theory; sequential codes; vector quantisation; adaptive universal quantization algorithm; adaptive universal vector quantization; convergence rates; delay; distortion-rate function; encoding; mean square error; sequence length; weighted sum; Adaptive algorithm; Convergence; Decoding; Delay; Encoding; Laboratories; Mean square error methods; Random number generation; Rate distortion theory; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on

Conference_Location

Trondheim

Print_ISBN

0-7803-2015-8

Type

conf

DOI

10.1109/ISIT.1994.395071

Filename

395071