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Logical Entropy of Dynamical Systems—A General Model

Logical entropy of dynamical systems -- a general model
Authors: Abolfazl Ebrahimzadeh; Zahra Eslami Giski; Dagmar Markechová;

Logical Entropy of Dynamical Systems—A General Model

Abstract

In the paper by Riečan and Markechová (Fuzzy Sets Syst. 96, 1998), some fuzzy modifications of Shannon’s and Kolmogorov-Sinai’s entropy were studied and the general scheme involving the presented models was introduced. Our aim in this contribution is to provide analogies of these results for the case of the logical entropy. We define the logical entropy and logical mutual information of finite partitions on the appropriate algebraic structure and prove basic properties of these measures. It is shown that, as a special case, we obtain the logical entropy of fuzzy partitions studied by Markechová and Riečan (Entropy 18, 2016). Finally, using the suggested concept of entropy of partitions we define the logical entropy of a dynamical system and prove that it is the same for two dynamical systems that are isomorphic.

Related Organizations
Keywords

Measures of information, entropy, Statistical aspects of fuzziness, sufficiency, and information, dynamical system, m-preserving transformation, isomorphism, logical mutual information, QA1-939, logical entropy; logical mutual information; <i>m</i>-preserving transformation; dynamical system; isomorphism, Entropy and other invariants, isomorphism, classification in ergodic theory, logical entropy, Entropy and other invariants, Mathematics

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
15
Top 10%
Top 10%
Top 10%
gold