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Analysis of the Size of Antidictionary in DCA

Authors: Julien Fayolle;

Analysis of the Size of Antidictionary in DCA

Abstract

We analyze the lossless data compression scheme using antidictionary. Its principle is to build the dictionary of a set of words that do not occur in the text (minimal forbidden words). We prove here that the number of words in the antidictionary, i.e., minimum forbidden words, behaves asymptotically linearly in the length of the text under a memoryless model on the generation of texts. The linearity constant is explicited. We use methods from analytic combinatorics.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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