Lagrange Stability of Complex-Valued Memristor-Based Neural Networks

被引：0
|
作者：
Wang, Nengjie [1 ]
Li, Biwen [1 ]
机构：
[1] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Peoples R China
来源：
2017 14TH INTERNATIONAL WORKSHOP ON COMPLEX SYSTEMS AND NETWORKS (IWCSN) | 2017年
关键词：
complex-valued neural networks; memristor; Lagrange stability; TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we consider the Lagrange stability of complex-valued memristor-based neural networks. Based upon inequality techniques, several new criterions are proposed to ensure that the neural network is Lagrange exponentially stable, and this can be achieved by means of constructing an appropriate function. Meanwhile, the attractive domain is estimated. The results improve the quality of extensive literature. To verify the feasibility of the derived results, a numerical example was given.
引用
收藏
页码：144 / 148
页数：5
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