Global Stability of Complex-Valued Neural Networks with Time-Delays and Impulsive Effects

被引：0
|
作者：
Zhang, Dongwen [1 ]
Jiang, Haijun [1 ]
Hu, Cheng [1 ]
Yu, Zhiyong [1 ]
Huang, Da [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
来源：
NEURAL INFORMATION PROCESSING (ICONIP 2017), PT III | 2017年 / 10636卷
关键词：
Stability criterion; Neural networks; Time delays;
D O I：
10.1007/978-3-319-70090-8_84
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The global exponential stability problem for a class of complex-valued recurrent neural networks with both asynchronous time-varying delays and impulse is concerned in this paper. By using Schur complement and Lyapunov functional, some new sufficient criteria to ascertain globally exponential stability of the equilibrium point are obtained in terms of linear matrix inequality. An example is given to illustrate the effectiveness of the results.
引用
收藏
页码：825 / 835
页数：11
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