Journal of Zhejiang University SCIENCE A 2026 Vol.27 No.7 P.762-778

http://doi.org/10.1631/jzus.A2600099


Dynamics of a two-disk dynamo loaded with a dual neuron circuit and its application


Author(s):  Fuqiang WU, Ying XU, Huimin QI, Jun MA

Affiliation(s):  1. School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, China more

Corresponding email(s):   alexwutian@nxu.edu.cn

Key Words:  Nonlinear dynamics, Neuron, Chaotic model, Electromechanical system, Memristor, Encryption


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Fuqiang WU, Ying XU, Huimin QI, Jun MA. Dynamics of a two-disk dynamo loaded with a dual neuron circuit and its application[J]. Journal of Zhejiang University Science A, 2026, 27(7): 762-778.

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Abstract: 
Constructing a neuromorphic electromechanical system based on a flexible memristor is of great significance for the development of biomimetic electrical-mechanical transverters. A bioinspired electromechanical system can perform real-time energy-efficient processing of multimodal signals, including electrical activities and mechanical motions. Here, we propose a bioinspired electromechanical system composed of a two-disc dynamo driven by a dual integrate-and-fire neuron. A memristive system exists in the bioinspired electromechanical system, as observed in the current–voltage relationship. The neuromorphic electromechanical model can exhibit a multiscroll hidden attractor by adjusting a controllable parameter. Complex chaotic behaviors have been demonstrated by numerical simulations, including two-parameter bifurcation, Lyapunov exponents, and phase diagrams. Finally, the applicability of a chaotic encryption scheme is successfully implemented on a neuromorphic electromechanical system.

神经元电路驱动机电系统的动力学及其应用

作者:吴富强1,2,徐莹3,祁慧敏1,马军4
机构:1宁夏大学,数学与统计学院,中国银川,750021;2宁夏数学基础科学研究中心,中国银川,750021;3山东师范大学,数学与统计学院,中国济南,250014;4兰州理工大学,物理系,中国兰州,730050
目的:构建基于忆阻器的神经形态机电模型对仿生机电系统的发展具有重要意义,而现有研究关于双盘发电机与积分放电神经元相结合的研究较少。本文旨在构建一种基于双盘发电机和双积分放电神经元的仿生神经形态机电系统,探究其复杂动力学行为,并基于该系统设计混沌图像加密方案,为相关领域的实际应用提供新路径。
创新点:1.将双盘发电机与双积分放电神经元模型相结合,构建一个自治神经形态机电系统,实现神经电活动与机械运动的耦合模拟;2.所构建的系统可通过调节可控参数呈现多卷隐藏吸引子,丰富具有隐藏吸引子的混沌系统;3.基于该神经形态机电系统生成的混沌序列设计了一种新型混沌图像加密方案,提升了信息加密的安全性与可靠性。
方法:1.通过分析系统的电流-电压关系,验证所构建的仿生机电系统中具有的忆阻特性;2.采用数值模拟方法,通过双参数分岔、李雅普诺夫指数和相图等分析手段,验证系统的复杂混沌行为;3.基于系统生成的混沌序列设计图像加密方案,并通过相关测试验证该加密算法的性能与安全性。
结论:1.构建的神经形态机电系统具有丰富复杂的动力学行为,可呈现多卷隐藏吸引子,能有效模拟神经电活动与机械运动耦合的非线性特性;2.基于该系统设计的混沌图像加密方案具有高信息熵和强密钥敏感性,可保证信息保护的可靠安全性;3.本研究不仅丰富了混沌系统类型,还为实际加密应用提供了有前景的混沌载体,在人工触觉装置、智能传感和安全通信领域具有良好应用前景,可推动相关领域的跨学科研究。

关键词:非线性动力学;神经元;混沌模型;机电系统;忆阻器;加密

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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Full Text:   <615>

Summary:  <64>

Suppl. Mater.: 

CLC number: 

On-line Access: 2026-07-20

Received: 2026-03-01

Revision Accepted: 2026-04-22

Crosschecked: 2026-07-20

Cited: 0

Clicked: 484

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Fu-qiang Wu

https://orcid.org/0000-0002-3850-7400

Jun Ma

https://orcid.org/0000-0002-6127-000X

Huimin QI

https://orcid.org/0009-0000-9433-8130

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