Title
Randomized Quantization and Source Coding With Constrained Output Distribution.
Abstract
This paper studies fixed-rate randomized vector quantization under the constraint that the quantizer's output has a given fixed probability distribution. A general representation of randomized quantizers that includes the common models in the literature is introduced via appropriate mixtures of joint probability measures on the product of the source and reproduction alphabets. Using this representation and results from optimal transport theory, the existence of an optimal (minimum distortion) randomized quantizer having a given output distribution is shown under various conditions. For sources with densities and the mean square distortion measure, it is shown that this optimum can be attained by randomizing quantizers having convex codecells. For stationary and memoryless source and output distributions a rate-distortion theorem is proved, providing a single-letter expression for the optimum distortion in the limit of large block-lengths.
Year
DOI
Venue
2013
10.1109/TIT.2014.2373382
IEEE Transactions on Information Theory
Keywords
DocType
Volume
memoryless systems,random codes,rate distortion theory,source coding,statistical distributions,vector quantisation,constrained output distribution,convex codecells,fixed-rate random vector quantization,mean square distortion measurement,memoryless source,optimal transport theory,probability distribution,rate distortion theorem,reproduction alphabet,source coding,Source coding,output-constrained distortion-rate function,quantization,random coding,randomization
Journal
61
Issue
ISSN
Citations 
1
0018-9448
1
PageRank 
References 
Authors
0.36
13
3
Name
Order
Citations
PageRank
Naci Saldi12910.27
Tamás Linder261768.20
Serdar Yüksel345753.31