Allerton 2015 Paper Abstract


Paper ThC2.4

Kostina, Victoria (California Institute of Technology)

Data compression with low distortion and finite blocklength

Scheduled for presentation during the Invited Session "Recent Developments in Information Theory, Statistics and Probability I" (ThC2), Thursday, October 1, 2015, 14:30−14:50, Solarium

53rd Annual Allerton Conference on Communication, Control, and Computing, Sept 29-Oct 2, 2015, Allerton Park and Retreat Center, Monticello, IL, USA

This information is tentative and subject to change. Compiled on December 5, 2021

Keywords Information Theory, Source Coding and Compression


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.



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