Universal Coding of Non-Prefix Context Tree Sources

  • Yuri M. Shtarkov
Chapter

Abstract

The efficiency of data compression with the help of universal coding depends on the used model or set of models of the source. By expanding the set of models and/or increasing their complexity we can improve the approximation of the statistical properties of messages. However, this entails a higher redundancy and (usually) a higher complexity of coding. For this reason, the development of comparatively simple models capable of improving the statistical description of messages is of great importance. Not surprisingly, this problem has attracted much attention.

Keywords

Conditional Probability Markov Chain Model Minimal Description Length Sequential Estimation Conditional Probability Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Yuri M. Shtarkov
    • 1
  1. 1.Institute for Problems of Information Transmission, RASMoscowRussia

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