DocumentCode
1010468
Title
Universal compression of memoryless sources over unknown alphabets
Author
Orlitsky, Alon ; Santhanam, Narayana P. ; Zhang, Junan
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of California, La Jolla, CA, USA
Volume
50
Issue
7
fYear
2004
fDate
7/1/2004 12:00:00 AM
Firstpage
1469
Lastpage
1481
Abstract
It has long been known that the compression redundancy of independent and identically distributed (i.i.d.) strings increases to infinity as the alphabet size grows. It is also apparent that any string can be described by separately conveying its symbols, and its pattern-the order in which the symbols appear. Concentrating on the latter, we show that the patterns of i.i.d. strings over all, including infinite and even unknown, alphabets, can be compressed with diminishing redundancy, both in block and sequentially, and that the compression can be performed in linear time. To establish these results, we show that the number of patterns is the Bell number, that the number of patterns with a given number of symbols is the Stirling number of the second kind, and that the redundancy of patterns can be bounded using results of Hardy and Ramanujan on the number of integer partitions. The results also imply an asymptotically optimal solution for the Good-Turing probability-estimation problem.
Keywords
data compression; redundancy; source coding; Bell number; Good-Turing probability-estimation problem; Stirling number; asymptotically optimal solution; compression redundancy; i.i.d.; independent and identically distributed strings; integer partitions; memoryless sources; pattern number; universal compression; unknown alphabets; Computer science; Encoding; Entropy; H infinity control; Image coding; Information theory; Pixel; Probability distribution;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2004.830761
Filename
1306545
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