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A Hidden Chaotic System with Multiple Attractors

This paper reports a hidden chaotic system without equilibrium point. The proposed system is studied by the software of MATLAB R2018 through several numerical methods, including Largest Lyapunov exponent, bifurcation diagram, phase diagram, Poincaré map, time-domain waveform, attractive basin and Sp...

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Detalles Bibliográficos
Autores principales: Zhang, Xiefu, Tian, Zean, Li, Jian, Wu, Xianming, Cui, Zhongwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534533/
https://www.ncbi.nlm.nih.gov/pubmed/34682065
http://dx.doi.org/10.3390/e23101341
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author Zhang, Xiefu
Tian, Zean
Li, Jian
Wu, Xianming
Cui, Zhongwei
author_facet Zhang, Xiefu
Tian, Zean
Li, Jian
Wu, Xianming
Cui, Zhongwei
author_sort Zhang, Xiefu
collection PubMed
description This paper reports a hidden chaotic system without equilibrium point. The proposed system is studied by the software of MATLAB R2018 through several numerical methods, including Largest Lyapunov exponent, bifurcation diagram, phase diagram, Poincaré map, time-domain waveform, attractive basin and Spectral Entropy. Seven types of attractors are found through altering the system parameters and some interesting characteristics such as coexistence attractors, controllability of chaotic attractor, hyperchaotic behavior and transition behavior are observed. Particularly, the Spectral Entropy algorithm is used to analyze the system and based on the normalized values of Spectral Entropy, the state of the studied system can be identified. Furthermore, the system has been implemented physically to verify the realizability.
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spelling pubmed-85345332021-10-23 A Hidden Chaotic System with Multiple Attractors Zhang, Xiefu Tian, Zean Li, Jian Wu, Xianming Cui, Zhongwei Entropy (Basel) Article This paper reports a hidden chaotic system without equilibrium point. The proposed system is studied by the software of MATLAB R2018 through several numerical methods, including Largest Lyapunov exponent, bifurcation diagram, phase diagram, Poincaré map, time-domain waveform, attractive basin and Spectral Entropy. Seven types of attractors are found through altering the system parameters and some interesting characteristics such as coexistence attractors, controllability of chaotic attractor, hyperchaotic behavior and transition behavior are observed. Particularly, the Spectral Entropy algorithm is used to analyze the system and based on the normalized values of Spectral Entropy, the state of the studied system can be identified. Furthermore, the system has been implemented physically to verify the realizability. MDPI 2021-10-14 /pmc/articles/PMC8534533/ /pubmed/34682065 http://dx.doi.org/10.3390/e23101341 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Xiefu
Tian, Zean
Li, Jian
Wu, Xianming
Cui, Zhongwei
A Hidden Chaotic System with Multiple Attractors
title A Hidden Chaotic System with Multiple Attractors
title_full A Hidden Chaotic System with Multiple Attractors
title_fullStr A Hidden Chaotic System with Multiple Attractors
title_full_unstemmed A Hidden Chaotic System with Multiple Attractors
title_short A Hidden Chaotic System with Multiple Attractors
title_sort hidden chaotic system with multiple attractors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534533/
https://www.ncbi.nlm.nih.gov/pubmed/34682065
http://dx.doi.org/10.3390/e23101341
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