Passivity and Robust Passivity of Delayed Cohen-Grossberg Neural Networks With and Without Reaction-Diffusion Terms

被引:15
作者
Chen, Weizhong [1 ]
Huang, Yanli [2 ]
Ren, Shunyan [3 ]
机构
[1] Tianjin Polytech Univ, Sch Comp Sci & Software Engn, Tianjin 300387, Peoples R China
[2] Tianjin Polytech Univ, Tianjin Key Lab Optoelect Detect Technol & Syst, Sch Comp Sci & Software Engn, Tianjin 300387, Peoples R China
[3] Tianjin Polytech Univ, Sch Mech Engn, Tianjin 300387, Peoples R China
基金
中国国家自然科学基金;
关键词
Cohen-Grossberg neural networks; Reaction-diffusion terms; Passivity; Robust passivity; GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; NONLINEAR-SYSTEMS; SYNCHRONIZATION; DISCRETE; STABILIZATION; DISSIPATIVITY; CRITERIA;
D O I
10.1007/s00034-017-0693-4
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we address the passivity and robust passivity problems for delayed Cohen-Grossberg neural networks (DCGNNs) both with and without reaction-diffusion terms. First, by resorting to appropriate Lyapunov functionals combined with some inequality techniques, some passivity conditions for DCGNNs without the reaction-diffusion terms are derived. Moreover, considering that parameter uncertainties may appear in neural networks, we also study the robust passivity of DCGNNs. In addition, we extend these derived results to the model of DCGNNs with reaction-diffusion terms. The validity and advantages of the theoretical results are demonstrated by three numerical examples.
引用
收藏
页码:2772 / 2804
页数:33
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