当前位置: X-MOL 学术Neural Process Lett. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Exponential Synchronization of Complex-Valued Neural Networks Via Average Impulsive Interval Strategy
Neural Processing Letters ( IF 3.1 ) Pub Date : 2020-08-01 , DOI: 10.1007/s11063-020-10309-5
Mei Liu , Zhanfeng Li , Haijun Jiang , Cheng Hu , Zhiyong Yu

In this paper, the issue of the exponential synchronization for complex-valued neural networks with both discrete and distributed delays is investigated by applying impulsive control protocol. Based on the Lyapunov–Krasovskii function, average impulsive interval as well as the comparison principle, some simple verifiable sufficient criteria are established to guarantee the exponential synchronization between the master and the slave systems. Meanwhile, through the serious analysis of the networks systems, the exponential convergence rate can be specified. Additionally, a numerical example is finally given to illustrate the effectiveness of the proposed theoretical results.



中文翻译:

基于平均脉冲间隔策略的复值神经网络指数同步

本文采用脉冲控制协议研究了具有离散和分布时滞的复值神经网络的指数同步问题。基于Lyapunov–Krasovskii函数,平均脉冲间隔以及比较原理,建立了一些简单的可验证的充分标准,以保证主系统和从系统之间的指数同步。同时,通过认真分析网络系统,可以确定指数收敛速度。另外,最后给出了一个数值例子来说明所提出的理论结果的有效性。

更新日期:2020-08-01
down
wechat
bug