DocumentCode
1780398
Title
Cumulant generating function of codeword lengths in optimal lossless compression
Author
Courtade, Thomas A. ; Verdu, Sergio
Author_Institution
EECS Dept., Univ. of California, Berkeley, Berkeley, CA, USA
fYear
2014
fDate
June 29 2014-July 4 2014
Firstpage
2494
Lastpage
2498
Abstract
This paper analyzes the distribution of the codeword lengths of the optimal lossless compression code without prefix constraints both in the non-asymptotic regime and in the asymptotic regime. The technique we use is based on upper and lower bounding the cumulant generating function of the optimum codeword lengths. In the context of prefix codes, the normalized version of this quantity was proposed by Campbell in 1965 as a generalized average length. We then use the one-shot bounds to analyze the large deviations (reliability function) and small deviations (normal approximation) of the asymptotic fundamental limit in the case of memoryless sources. In contrast to other approaches based on the method of types or the Berry-Esséen inequality, we are able to deal with sources with infinite alphabets.
Keywords
approximation theory; constraint theory; data compression; function approximation; higher order statistics; reliability theory; Berry-Esséen inequality; asymptotic fundamental limit; cumulant generating function; generalized average length; large deviation; memoryless sources; nonasymptotic regime; normal approximation; one-shot bound; optimal lossless compression code; optimum codeword length; prefix code; prefix constraint; reliability function; small deviation; Context; Convergence; Entropy; Information theory; Random variables; Reliability theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory (ISIT), 2014 IEEE International Symposium on
Conference_Location
Honolulu, HI
Type
conf
DOI
10.1109/ISIT.2014.6875283
Filename
6875283
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