Multi-scroll Hopfield neural network under electromagnetic radiation and its brain-like coupling synchronization

Frontiers in Physics

Physics

Xia Wang¹  Xiaojing Cao¹  Haiyang Gu²  Zhengjun Yao³  Sen Fu⁴ 

[1] Aircraft Technology Branch of Hunan Aerospace Co., Ltd., Changsha, China;China Aerospace Science and Industry Corporation, Beijing, China;College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China;College of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China;Aircraft Technology Branch of Hunan Aerospace Co., Ltd., Changsha, China;China Aerospace Science and Industry Corporation, Beijing, China;

关键词: memristor;    Hopfield neural network (HNN);    multi-scroll;    multistability;    synchronization;   

DOI  :  10.3389/fphy.2023.1252568

 received in 2023-07-04, accepted in 2023-08-15,  发布年份 2023

来源: Frontiers

【 摘 要 】

Multi-scroll attractors have attracted attention because of their more complex topological structures and artificially controllable attractor structures. This paper proposes a new nonvolatile magnetic-controlled memristor and uses it to simulate the effect of membrane flux changes caused by neuronal exposure to electromagnetic radiation. A series of complex chaotic phenomena are found by plotting phase diagrams, bifurcation diagrams, attractor domains and 01 tests, including multi-scroll chaotic attractors controlled by memristors, symmetric bifurcation behavior, coexistence phenomena enhanced by initial offset. The mechanisms behind them are explained through equilibrium point analysis. A dual memristive HNN (MHNN) coupling synchronization model is proposed to simulate the synchronization between regions within the human brain. The Lyapunov function of the error is constructed to prove that this coupling synchronization scheme is ultimately bounded. The feasibility of this synchronization scheme is verified by establishing a Simulink model and conducting simulation experiments.

【 授权许可】

Unknown   
Copyright © 2023 Fu, Wang, Gu, Cao and Yao.