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A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis
When chaotic systems are used in different practical applications, such as chaotic secure communication and chaotic pseudorandom sequence generators, a large number of chaotic systems are strongly required. However, for a lack of a systematic construction theory, the construction of chaotic systems...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515155/ https://www.ncbi.nlm.nih.gov/pubmed/33267372 http://dx.doi.org/10.3390/e21070658 |
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author | Wang, Chuanfu Ding, Qun |
author_facet | Wang, Chuanfu Ding, Qun |
author_sort | Wang, Chuanfu |
collection | PubMed |
description | When chaotic systems are used in different practical applications, such as chaotic secure communication and chaotic pseudorandom sequence generators, a large number of chaotic systems are strongly required. However, for a lack of a systematic construction theory, the construction of chaotic systems mainly depends on the exhaustive search of systematic parameters or initial values, especially for a class of dynamical systems with hidden chaotic attractors. In this paper, a class of quadratic polynomial chaotic maps is studied, and a general method for constructing quadratic polynomial chaotic maps is proposed. The proposed polynomial chaotic maps satisfy the Li–Yorke definition of chaos. This method can accurately control the amplitude of chaotic time series. Through the existence and stability analysis of fixed points, we proved that such class quadratic polynomial maps cannot have hidden chaotic attractors. |
format | Online Article Text |
id | pubmed-7515155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75151552020-11-09 A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis Wang, Chuanfu Ding, Qun Entropy (Basel) Article When chaotic systems are used in different practical applications, such as chaotic secure communication and chaotic pseudorandom sequence generators, a large number of chaotic systems are strongly required. However, for a lack of a systematic construction theory, the construction of chaotic systems mainly depends on the exhaustive search of systematic parameters or initial values, especially for a class of dynamical systems with hidden chaotic attractors. In this paper, a class of quadratic polynomial chaotic maps is studied, and a general method for constructing quadratic polynomial chaotic maps is proposed. The proposed polynomial chaotic maps satisfy the Li–Yorke definition of chaos. This method can accurately control the amplitude of chaotic time series. Through the existence and stability analysis of fixed points, we proved that such class quadratic polynomial maps cannot have hidden chaotic attractors. MDPI 2019-07-04 /pmc/articles/PMC7515155/ /pubmed/33267372 http://dx.doi.org/10.3390/e21070658 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Chuanfu Ding, Qun A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title | A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title_full | A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title_fullStr | A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title_full_unstemmed | A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title_short | A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis |
title_sort | class of quadratic polynomial chaotic maps and their fixed points analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515155/ https://www.ncbi.nlm.nih.gov/pubmed/33267372 http://dx.doi.org/10.3390/e21070658 |
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