Asymptotic Optimality of Antidictionary Codes

Details Asymptotic Optimality of Antidictionary Codes Asymptotic Optimality of Antidictionary Codes

2010-06-02

arxiv.org/abs/1006.0284v1

Computer Science

Information Theory

5 pages, to appear in the proceedings of 2010 IEEE International Symposium on Information Theory (ISIT2010)

Scientific paper

An antidictionary code is a lossless compression algorithm using an antidictionary which is a set of minimal words that do not occur as substrings in an input string. The code was proposed by Crochemore et al. in 2000, and its asymptotic optimality has been proved with respect to only a specific information source, called balanced binary source that is a binary Markov source in which a state transition occurs with probability 1/2 or 1. In this paper, we prove the optimality of both static and dynamic antidictionary codes with respect to a stationary ergodic Markov source on finite alphabet such that a state transition occurs with probability $p (0 < p \leq 1)$.

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