A universal data compression system

Authors:
J. Rissanen
Affiliations:
-
Venue:
IEEE Transactions on Information Theory
Year:
2006

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Abstract

A universal data compression algorithm is described which is capable of compressing long strings generated by a "finitely generated" source, with a near optimum per symbol length without prior knowledge of the source. This class of sources may be viewed as a generalization of Markov sources to random fields. Moreover, the algorithm does not require a working storage much larger than that needed to describe the source generating parameters.