New Results on Exponential Stability of Competitive Neural Networks with Multi-Proportional Delays

被引：13
|
作者：
Qin, Jiali [1 ]
Li, Yongkun [1 ]
机构：
[1] Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China
来源：
ASIAN JOURNAL OF CONTROL | 2020年 / 22卷 / 02期
关键词：
Competitive neural networks; proportional delays; exponential stability; TIME-VARYING DELAYS; ANTIPERIODIC SOLUTIONS; PERIODIC-SOLUTION; SYNCHRONIZATION; LEAKAGE;
D O I：
10.1002/asjc.1926
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we are concerned with a class of competitive neural networks with multi-proportional delays. By applying the Banach fixed point theorem and constructing suitable Lyapunov functions, we obtain new sufficient conditions for the global exponential stability to this class of neural networks, which are easily verifiable. Finally, two examples are given to illustrate the effectiveness of the obtained results.
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页码：750 / 760
页数：11
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