Title :
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
fDate :
27 Jun-1 Jul 1994
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;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.395071
