High-resolution functional quantization

Vinith Misra, Vivek K. Goyal, Lav R Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Suppose a function of N real source variables X1N = (X1, X2, ..., XN) is desired at a destination constrained to receive a limited number of bits. If the result of evaluating the function, Y = G(X1N), can be itself encoded, this is the optimal strategy - the origin of Y becomes irrelevant to the communication problem. We consider two alternative scenarios: distributed quantization, in which each Xi must be separately encoded: and linear transform coding of X1N. Optimal fixed- and variable-rate scalar quantizers are derived under the conventional assumptions of high-resolution quantization theory, and we find optimal transforms for transform coding. For certain classes of functions, examples demonstrate large improvements over using quantizers designed to minimize distortion of the XiS.

Original languageEnglish (US)
Title of host publicationProceedings - 2008 Data Compression Conference, DCC 2008
Number of pages10
StatePublished - 2008
Externally publishedYes
Event2008 Data Compression Conference, DCC 2008 - Snowbird, UT, United States
Duration: Mar 25 2008Mar 27 2008

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Other2008 Data Compression Conference, DCC 2008
Country/TerritoryUnited States
CitySnowbird, UT

ASJC Scopus subject areas

  • Computer Networks and Communications


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