Anti-synchronization Analysis and Pinning Control of Coupled Neural Networks with Multiple Weights

被引：0
作者：
Hou, Jie [1 ]
Huang, Yan-Li [1 ]
Wang, Jin-Liang [1 ]
Ren, Shun-Yan [2 ]
Liu, Dong-Fang [3 ]
机构：
[1] Tianjin Polytech Univ, Sch Comp Sci & Software Engn, Tianjin 300387, Peoples R China
[2] Tianjin Polytech Univ, Sch Mech Engn, Tianjin 300387, Peoples R China
[3] Tianjin Tianhang Wisdom Technol Co Ltd, Tianjin 300452, Peoples R China
来源：
2018 IEEE 8TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (IEEE-CYBER) | 2018年
基金：
中国国家自然科学基金;
关键词：
COMPLEX NETWORKS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the multi-weighted coupled neural networks (MWCNN) models with and without delayed coupling are studied. First, we analyze the anti-synchronization of the proposed network models by using Lyapunov functional method and some inequality techniques, and give some anti synchronization conditions for MWCNN. In addition, several anti-synchronization criteria are established via the pinning adaptive techniques. Lastly, an example is presented to illustrate the effectiveness and correctness of the results we obtained.
引用
收藏
页码：895 / 900
页数：6
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