DocumentCode :
940127
Title :
On universal quantization
Author :
Ziv, Jacob
Volume :
31
Issue :
3
fYear :
1985
fDate :
5/1/1985 12:00:00 AM
Firstpage :
344
Lastpage :
347
Abstract :
The quantization of 
-dimensional vectors in 
with an arbitrary probability measure, under a mean-square error constraint, is discussed. It is demonstrated that a uniform, one-dimensional quantizer followed by a noiseless digital variable-rate encoder ("entropy encoding") can yield a rate that is, for any , no more than 
bit-per-sample higher than the rate associated with the optimal -dimensionai quantizer, regardless of the probabilistic characterization of the input -vector for the allowable mean-square error.
-dimensional vectors in with an arbitrary probability measure, under a mean-square error constraint, is discussed. It is demonstrated that a uniform, one-dimensional quantizer followed by a noiseless digital variable-rate encoder ("entropy encoding") can yield a rate that is, for any , no more than bit-per-sample higher than the rate associated with the optimal -dimensionai quantizer, regardless of the probabilistic characterization of the input -vector for the allowable mean-square error.Keywords :
Source coding; Binary sequences; Entropy; Jacobian matrices; Lattices; Probability density function; Quantization;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1985.1057034
Filename :
1057034
Link To Document :
