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Chaos Theory and Applications
Article . 2022 . Peer-reviewed
Data sources: Crossref
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Chaos Theory and Applications
Article . 2022
Data sources: DOAJ
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Lyapunov Exponent Enhancement in Chaotic Maps with Uniform Distribution Modulo One Transformation

Authors: Günyaz ABLAY;

Lyapunov Exponent Enhancement in Chaotic Maps with Uniform Distribution Modulo One Transformation

Abstract

Most of the chaotic maps are not suitable for chaos-based cryptosystems due to their narrow chaotic parameter range and lacking of strong unpredictability. This work presents a nonlinear transformation approach for Lyapunov exponent enhancement and robust chaotification in discrete-time chaotic systems for generating highly independent and uniformly distributed random chaotic sequences. The outcome of the new chaotic systems can directly be used in random number and random bit generators without any post-processing algorithms for various information technology applications. The proposed Lyapunov exponent enhancement based chaotic maps are analyzed with Lyapunov exponents, bifurcation diagrams, entropy, correlation and some other statistical tests. The results show that excellent random features can be accomplished even with one-dimensional chaotic maps with the proposed approach.

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Turkey
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Keywords

T57-57.97, cryptography, Applied mathematics. Quantitative methods, chaos, lyapunov exponent, Random numbers, chaos;Lyapunov exponent;Random numbers;Cryptography;image encryption, image encryption, QA75.5-76.95, Image encryption, Electronic computers. Computer science, Cryptography, Chaos, Lyapunov exponent, random numbers

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selected citations
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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!
views
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