Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations

被引:19
作者
Duan, Lian [1 ]
Huang, Lihong [2 ]
Guo, Zhenyuan [3 ]
机构
[1] Anhui Univ Sci & Technol, Sch Sci, Huainan, Anhui 232001, Peoples R China
[2] Changsha Univ Sci & Technol, Sch Math & Stat, Changsha 410114, Hunan, Peoples R China
[3] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; POINT DISSIPATIVITY; CONVERGENCE; PERIODICITY;
D O I
10.1063/1.4945798
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations. (C) 2016 AIP Publishing LLC.
引用
收藏
页数:13
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