FPGA Implementation for a Class of Generalized Hamiltonian Conservative Chaotic Systems Based on Integrated 4D Euler Equations with Multistability.
Published In: International Journal of Bifurcation & Chaos in Applied Sciences & Engineering, 2024, v. 34, n. 15. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Jia, Hongyan; Li, Wei; Wang, Hejin; Han, Xiaoguang; Wang, Shiming 3 of 3
Abstract
In this paper, two newly proposed generalized Hamiltonian Conservative Chaotic Systems (CCSs) based on integrated 4D Euler equations are first discussed. Second, another generalized Hamiltonian CCS is also proposed. Furthermore, a class of generalized Hamiltonian CCSs based on integrated 4D Euler equations is given and studied. Subsequently, numerical analysis for the class of generalized Hamiltonian CCSs is further investigated to show their advantages over most of the existing CCSs, where the corresponding Lyapunov exponents' diagrams, bifurcation diagrams and phase portraits are all given to show their multistability and complex dynamics. Finally, the class of generalized Hamiltonian CCSs is implemented by using FPGA technology, and the results observed in FPGA implementation are consistent with those observed in the numerical analysis. All these results not only show multistability from a physical point of view, but also provide new physical models for chaos applications. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Bifurcation & Chaos in Applied Sciences & Engineering. 2024/12, Vol. 34, Issue 15, p1
- Document Type:Article
- Subject Area:Science
- Publication Date:2024
- ISSN:0218-1274
- DOI:10.1142/S0218127424501888
- Accession Number:181578986
- Copyright Statement:Copyright of International Journal of Bifurcation & Chaos in Applied Sciences & Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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