New algebraic conditions for ISS of memristive neural networks with variable delays

被引：10
|
作者：
Zhong, Kai [1 ]
Yang, Qiqi [1 ]
Zhu, Song [1 ]
机构：
[1] China Univ Min & Technol, Coll Sci, Xuzhou 221116, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2017年 / 28卷 / 08期
关键词：
Input-to-state stability; Memristive neural network; Variable delays; GLOBAL EXPONENTIAL STABILITY; TO-STATE STABILITY; ASYMPTOTIC STABILITY; DEPENDENT STABILITY; ROBUSTNESS ANALYSIS; NONLINEAR-SYSTEMS; TIME; SYNCHRONIZATION; DISCRETE; STABILIZATION;
D O I：
10.1007/s00521-016-2176-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a general class of memristive neural networks with variable delays is studied. By utilizing control theory and nonsmoooth analysis, two sufficient criteria ensuring input-to-state stability of memristive neural networks with variable delays are firstly obtained which are novel and more practical than the previous works in the literature. Finally, a numerical example is given to demonstrate the effectiveness of our results.
引用
收藏
页码：2089 / 2097
页数：9
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