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Open AccessJournal ArticleDOI

Entropy of Fuzzy Partitions and Entropy of Fuzzy Dynamical Systems

Dagmar Markechová, +1 more
- 18 Jan 2016 - 
- Vol. 18, Iss: 1, pp 19
TLDR
An analogy of the Kolmogorov–Sinai Theorem on generators is proved for fuzzy dynamical systems because it is shown that different definitions of the entropy of fuzzy partitions lead to different notions of entropies of fuzzy dynamicals systems.
Abstract
In the paper we define three kinds of entropy of a fuzzy dynamical system using different entropies of fuzzy partitions. It is shown that different definitions of the entropy of fuzzy partitions lead to different notions of entropies of fuzzy dynamical systems. The relationships between these entropies are studied and connections with the classical case are mentioned as well. Finally, an analogy of the Kolmogorov–Sinai Theorem on generators is proved for fuzzy dynamical systems.

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Citations
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Journal ArticleDOI

Logical Entropy of Fuzzy Dynamical Systems

TL;DR: The chain rules for logical entropy and for logical mutual information of fuzzy partitions are established and it is proved that the logical entropy of fuzzy dynamical systems is invariant under isomorphism of fuzzy dynamic systems.
Journal ArticleDOI

Weighted Regression-Based Extremum Response Surface Method for Structural Dynamic Fuzzy Reliability Analysis

Cheng Lu, +2 more
- 26 Apr 2019 - 
TL;DR: In this paper, a weighted regression-based extremum response surface method (WR-ERSM) is proposed to improve structural dynamic fuzzy reliability analysis, by considering the randomness of design parameters and the fuzziness of the safety criterion.
Journal ArticleDOI

Logical Entropy of Dynamical Systems—A General Model

TL;DR: Using the suggested concept of entropy of partitions, the logical entropy of a dynamical system is defined and it is proved that it is the same for two dynamical systems that are isomorphic.
Journal ArticleDOI

Logical Entropy and Logical Mutual Information of Experiments in the Intuitionistic Fuzzy Case

TL;DR: The concepts of logical entropy and logical mutual information of experiments in the intuitionistic fuzzy case are introduced, and an analogy of the Kolmogorov-Sinai theorem on generators for IF-dynamical systems is proved.
Journal ArticleDOI

Logical entropy of dynamical systems

TL;DR: It is shown that by replacing the Shannon entropy function by the logical entropy function the authors obtain the results analogous to the case of classical Kolmogorov–Sinai entropy theory of dynamical systems.
References
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A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
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Probability measures of Fuzzy events

TL;DR: In probability theory, an event, A, is a member of a a-field, CY, of subsets of a sample space ~2, where CY is any collection of disjoint events.
Book

Intuitionistic Fuzzy Sets: Theory and Applications

TL;DR: The basic definitions and properties of the Intuitionistic Fuzzy Sets (IFSs) are introduced in the book and readers will find discussions on some of the IFS extensions (for example, interval-values IFSs, temporal I FSs and others) and applications.
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TL;DR: Theories of ProbabilityFoundation of Probabilistic Logic ProgrammingGood ThinkingStatistical Foundations of Data ScienceFoundations of Risk Analysis foundations of Estimation Theory findations of the theory of probability.