Journal ArticleDOI
A universal data compression system
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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.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.read more
Citations
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Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing.
TL;DR: Simulated Annealing in practice as discussed by the authors : Simulated annealing is an algorithm for parallel simulated Annealing algorithms with Boltzmann machines, which can be found in the literature.
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The minimum description length principle in coding and modeling
TL;DR: The normalized maximized likelihood, mixture, and predictive codings are each shown to achieve the stochastic complexity to within asymptotically vanishing terms.
Journal ArticleDOI
Microbial gene identification using interpolated Markov models
TL;DR: A new system, GLIMMER, is described, which is more flexible and more powerful than fixed-order Markov methods, which have previously been the primary content-based technique for finding genes in microbial DNA.
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Universal coding, information, prediction, and estimation
TL;DR: A connection between universal codes and the problems of prediction and statistical estimation is established, and a known lower bound for the mean length of universal codes is sharpened and generalized, and optimum universal codes constructed.
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The context-tree weighting method: basic properties
TL;DR: The authors derive a natural upper bound on the cumulative redundancy of the method for individual sequences that shows that the proposed context-tree weighting procedure is optimal in the sense that it achieves the Rissanen (1984) lower bound.
References
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Journal ArticleDOI
Paper: Modeling by shortest data description
TL;DR: The number of digits it takes to write down an observed sequence x1,...,xN of a time series depends on the model with its parameters that one assumes to have generated the observed data.
Journal ArticleDOI
Compression of individual sequences via variable-rate coding
Jacob Ziv,A. Lempel +1 more
TL;DR: The proposed concept of compressibility is 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.
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Universal modeling and coding
Jorma Rissanen,G. Langdon +1 more
TL;DR: A general class of so-called first-in first-out (FIFO) arithmetic codes is described which require no alphabet extension devices and which therefore can be used in conjunction with the best models.