Exponential stability of non-autonomous delayed neural networks

被引：0
|
作者：
Zhang, Qiang [1 ]
Wei, Xiaopeng
Zhou, Dongsheng
Zhou, Changjun
机构：
[1] Dalian Univ, Liaoing Key Lab Intelligent Informat Proc, Dalian 116622, Liaoning, Peoples R China
[2] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Liaoning, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13卷
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D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Global exponential stability of non-autonomous delayed neural networks is analyzed. A new sufficient condition ensuring the exponential stability for this type of neural networks by employing the method of delay differential inequality. Since the condition does not impose differentiability on delay function, it is less conservative than some established in the earlier references. This approach is straightforward and effective for stability analysis for it does not resort to constructing any Lyapunov functionals.
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页码：581 / 583
页数：3
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