Title :
The universality and linearity of compression by substring enumeration
Author :
Dubé, Danny ; Yokoo, Hidetoshi
Author_Institution :
Univ. Laval, Quebec City, QC, Canada
fDate :
July 31 2011-Aug. 5 2011
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;
Conference_Titel :
Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
Conference_Location :
St. Petersburg
Print_ISBN :
978-1-4577-0596-0
Electronic_ISBN :
2157-8095
DOI :
10.1109/ISIT.2011.6033796