DocumentCode
3503775
Title
The universality and linearity of compression by substring enumeration
Author
Dubé, Danny ; Yokoo, Hidetoshi
Author_Institution
Univ. Laval, Quebec City, QC, Canada
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
1519
Lastpage
1523
Abstract
A new lossless data compression technique called compression by substring enumeration (CSE) has recently been introduced. Two conjectures have been stated in the original paper and they have not been proved there nor in subsequent papers on CSE. The first conjecture says that CSE is universal for Markovian sources, provided an appropriate predictor is devised. The second one says that CSE has a linear complexity both in time and in space. In this paper, we present an appropriate predictor and demonstrate that CSE indeed becomes universal for any order-k Markovian source. Finally, we prove that the compacted substring tree on which CSE´s linear complexity depends effectively has linear size.
Keywords
Markov processes; data compression; CSE; compression by substring enumeration; compression linearity; compression universality; linear complexity; lossless data compression technique; order-k Markovian source; Data compression; Encoding; Entropy; Flyback transformers; Probability distribution; Random variables; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
Conference_Location
St. Petersburg
ISSN
2157-8095
Print_ISBN
978-1-4577-0596-0
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2011.6033796
Filename
6033796
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