NDLI: Relative entropy and quantizer mismatch

Content Provider	IEEE Xplore Digital Library
Author	Gray, R.M. Linder, T.
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. Eng., Stanford Univ., CA, USA (Gray, R.M.)
Abstract	Mismatch in vector quantization or source coding is a measure of the performance loss resulting when a code optimized for one source is applied to another. In lossless compression, the relative entropy between the sources for which the code is designed and the source to which it is actually applied measures mismatch. Recent results in high rate vector quantization theory extend these ideas to the relative entropy between continuous distributions as a measure of quantizer mismatch. The results and some of their applications and examples are described, including the use of relative entropy in a distortion measure for Lloyd clustering for the design of Gauss mixture models and classified vector quantizers.
Starting Page	129
Ending Page	133
File Size	346701
Page Count	5
File Format	PDF
ISBN	0780375769
ISSN	10586393
DOI	10.1109/ACSSC.2002.1197162
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Entropy Decoding Image coding Particle measurements Lagrangian functions Performance loss Indium phosphide Distortion measurement Network address translation Mathematics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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