FPGA-based circuit realization of dynamics editing in a chaotic system

Abstract Multistability in chaotic systems is defined as the coexistence of multiple stable attractors within a system. Through the precise calibration of the system’s initial conditions, transitions between disparate stable states can be facilitated. Dynamics editing is an emerging method in dynamics management that aims to introduce appropriate piecewise-linear functions to extract various attractors in a dynamical system and consolidate them into the same phase space. This paper explores the implementation of both one-dimensional and two-dimensional dynamics editing, with a focus on FPGA hardware technology. This approach shows a promising potential for the deployment of chaos-optimized particle swarm optimization in embedded systems.

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Publication Details

Journal
Physica Scripta
Published
2025-05-27
DOI
https://doi.org/10.1088/1402-4896/addd72
Citations
3
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
7.44

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article

FPGA-based circuit realization of dynamics editing in a chaotic system

Wangyu Liu, Chunbiao Li, Haiyan Fu, Tengfei Lei et al.
3 citations
Physica Scripta
Neural Networks and Applications
7.44
article

FPGA-based circuit realization of dynamics editing in a chaotic system

Wangyu Liu, Chunbiao Li, Haiyan Fu, Tengfei Lei, Hai Zhang
article en
3 citations

Abstract

Abstract Multistability in chaotic systems is defined as the coexistence of multiple stable attractors within a system. Through the precise calibration of the system’s initial conditions, transitions between disparate stable states can be facilitated. Dynamics editing is an emerging method in dynamics management that aims to introduce appropriate piecewise-linear functions to extract various attractors in a dynamical system and consolidate them into the same phase space. This paper explores the implementation of both one-dimensional and two-dimensional dynamics editing, with a focus on FPGA hardware technology. This approach shows a promising potential for the deployment of chaos-optimized particle swarm optimization in embedded systems.

Physica ScriptaVol. 100(7)
Qilu University of Technology (CN), Nanjing University of Information Science and Technology (CN), Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Neural Networks and Applications
7.44
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