About: Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #71415 Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks
sameAs	Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks
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dc:hasVersion	Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks (PDF)
Title	Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2019-06
Creator	Jurgen Kurths Bingbing Feng Chengqing Li Guanrong Chen Shujun Li
status	peer reviewed published
Publisher	IEEE
abstract	Chaotic dynamics is widely used to design pseudorandom number generators and for other applications such as secure communications and encryption. This paper aims to study the dynamics of discrete-time chaotic maps in the digital (i.e., finite-precision) domain. Differing from the traditional approaches treating a digital chaotic map as a black box with different explanations according to the test results of the output, the dynamical properties of such chaotic maps are first explored with a fixed-point arithmetic, using the Logistic map and the Tent map as two representative examples, from a new perspective with the corresponding state-mapping networks (SMNs). In an SMN, every possible value in the digital domain is considered as a node and the mapping relationship between any pair of nodes is a directed edge. The scale-free properties of the Logistic map's SMN are proved. The analytic results are further extended to the scenario of floating-point arithmetic and for other chaotic maps. Understanding the network structure of a chaotic map's SMN in digital computers can facilitate counteracting the undesirable degeneration of chaotic dynamics in finite-precision domains, helping also classify and improve the randomness of pseudorandom number sequences generated by iterating chaotic maps.
Is Part Of	IEEE Transactions on Circuits and Systems I: Regular Papers https://kar.kent.ac.uk/id/repository
Subject	QA101 Arithmetic QA 75 Electronic computers. Computer science QA 76 Software, computer programming, QC20 Mathematical Physics
list of authors	https://kar.kent.ac.uk/id/eprint/71415#authors
issue	6
volume	66
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #71415 Dynamic Analysis of Digital Chaotic Maps via State-Mapping Networks

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