Advancing Chaos Theory: A Set-Valued Perspective on Multiple Mappings with Computational Detection Algorithms

Fuente: arXiv
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Hauptverfasser: Alvarez, Illych, Leon, Ivonne, Peña, Ivy
Format: Preprint
Veröffentlicht: 2024
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author Alvarez, Illych
Leon, Ivonne
Peña, Ivy
author_facet Alvarez, Illych
Leon, Ivonne
Peña, Ivy
contents This study redefines the analysis of Devaney chaos in multiple mappings from a set-valued perspective and introduces new conditions to characterize their chaotic behavior. As an innovative advancement, we develop computational algorithms to detect and visualize chaotic features such as transitivity and sensitivity. These algorithms provide tools to explore complex dynamics in higher-dimensional systems, validating theoretical concepts and opening new research avenues in chaos theory.
format Preprint
id arxiv_https___arxiv_org_abs_2409_17936
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Advancing Chaos Theory: A Set-Valued Perspective on Multiple Mappings with Computational Detection Algorithms
Alvarez, Illych
Leon, Ivonne
Peña, Ivy
Chaotic Dynamics
Functional Analysis
This study redefines the analysis of Devaney chaos in multiple mappings from a set-valued perspective and introduces new conditions to characterize their chaotic behavior. As an innovative advancement, we develop computational algorithms to detect and visualize chaotic features such as transitivity and sensitivity. These algorithms provide tools to explore complex dynamics in higher-dimensional systems, validating theoretical concepts and opening new research avenues in chaos theory.
title Advancing Chaos Theory: A Set-Valued Perspective on Multiple Mappings with Computational Detection Algorithms
topic Chaotic Dynamics
Functional Analysis
url https://arxiv.org/abs/2409.17936