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
Link To Document :
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