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Information, complexity and entropy: a new approach to theory and measurement methods

Vieri Benci·Claudio Bonanno·Stefano Galatolo·Giulia Menconi·Federico Ponchio
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Abstract

In this paper, we present some results on information, complexity and entropy as defined below and we discuss their relations with the Kolmogorov-Sinai entropy which is the most important invariant of a dynamical system. These results have the following features and motivations: -we give a new computable definition of information and complexity which allows to give a computable characterization of the K-S entropy; -these definitions make sense even for a single orbit and can be measured by suitable data compression algorithms; hence they can be used in simulations and in the analysis of experimental data; -the asymptotic behavior of these quantities allows to compute not only the Kolmogorov-Sinai entropy but also other quantities which give a measure of the chaotic behavior of a dynamical system even in the case of null entropy.

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Vieri Benci, Claudio Bonanno, Stefano Galatolo, Giulia Menconi, Federico Ponchio. 2001-07-10. Information, complexity and entropy: a new approach to theory and measurement methods. https://arxiv.org/abs/math/0107067

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