Data compression with low distortion and finite blocklength
- Creators
- Kostina, Victoria
Abstract
This paper considers lossy source coding of n-dimensional continuous memoryless sources with low mean-square error distortion and shows a simple, explicit approximation to the minimum source coding rate. More precisely, a nonasymptotic version of Shannon's lower bound is presented. Lattice quantizers are shown to approach that lower bound, provided that the source density is smooth enough and the distortion is low, which implies that fine multidimensional lattice coverings are nearly optimal in the rate-distortion sense even at finite n. The achievability proof technique avoids both the usual random coding argument and the simplifying assumption of the presence of a dither signal.
Additional Information
© 2015 IEEE. This work is supported by the Simons Institute for the Theory of Computing.
Attached Files
Submitted - 1510.02190v2.pdf
Files
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Additional details
- Eprint ID
- 66072
- DOI
- 10.1109/ALLERTON.2015.7447135
- Resolver ID
- CaltechAUTHORS:20160412-084329467
- arXiv
- arXiv:1510.02190
- URL
- https://resolver.caltech.edu/CaltechAUTHORS:20170308-161418854
- Simons Institute
- Created
-
2016-04-12Created from EPrint's datestamp field
- Updated
-
2021-11-10Created from EPrint's last_modified field