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Compression of individual sequences via variable-rate coding

IEEE Transactions on Information Theory · 1978 · Vol. 24(5) · pp. 530–536
J. ZivA. Lempel

Abstract

Compressibility of individual sequences by the class of generalized finite-state information-lossless encoders is investigated. These encoders can operate in a variable-rate mode as well as a fixed-rate one, and they allow for any finite-state scheme of variable-length-to-variable-length coding. For every individual infinite sequence <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</tex> a quantity <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\rho(x)</tex> is defined, called the compressibility of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</tex> , which is shown to be the asymptotically attainable lower bound on the compression ratio that can be achieved for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</tex> by any finite-state encoder. This is demonstrated by means of a constructive coding theorem and its converse that, apart from their asymptotic significance, also provide useful performance criteria for finite and practical data-compression tasks. The proposed concept of compressibility is also shown to play a role analogous to that of entropy in classical information theory where one deals with probabilistic ensembles of sequences rather than with individual sequences. While the definition of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\rho(x)</tex> allows a different machine for each different sequence to be compressed, the constructive coding theorem leads to a universal algorithm that is asymptotically optimal for all sequences.

Algorithms and Data CompressionComputability, Logic, AI AlgorithmsCellular Automata and ApplicationsEncoderLossless compressionCoding (social sciences)Information theoryEntropy (arrow of time)ConverseComputer scienceDiscrete mathematicsData compressionAlgorithm
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References
On the Complexity of Finite Sequences
IEEE Transactions on Information Theory · 1976 · 2,712 citations
A universal algorithm for sequential data compression
IEEE Transactions on Information Theory · 1977 · 5,424 citations
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