• 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