Asymptotic and finite-time cluster synchronization of neural networks via two different controllers

Author:

Cao Juan1,Ren Fengli1,Zhou Dacheng2

Affiliation:

1. Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, MO 210016, China

2. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, MO 200444, China

Abstract

<p style='text-indent:20px;'>In this paper, by using a pinning impulse controller and a hybrid controller respectively, the research difficulties of asymptotic synchronization and finite time cluster synchronization of time-varying delayed neural networks are studied. On the ground of Lyapunov stability theorem and Lyapunov-Razumikhin method, a novel sufficient criterion on asymptotic cluster synchronization of time-varying delayed neural networks is obtained. Utilizing Finite time stability theorem and hybrid control technology, a sufficient criterion on finite-time cluster synchronization is also obtained. In order to deal with time-varying delay and save control cost, pinning pulse control is introduced to promote the realization of asymptotic cluster synchronization. Following the idea of pinning control scheme, we design a progressive hybrid control to promote the realization of finite time cluster synchronization. Finally, an example is given to illustrate the theoretical results.</p>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Finite-time cluster synchronization of multi-weighted fractional-order coupled neural networks with and without impulsive effects;Neural Networks;2024-12

2. A Study of Nanosecond Clock Synchronization Methods for Real-Time Transient Simulation;2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE);2024-05-10

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