Mean square exponential stability of stochastic delay cellular neural networks

被引:0
|
作者
Guo, Yingxin [1 ,2 ]
机构
[1] Zhejiang Univ, Dept Control Engn, Inst Cyber Syst & Control, Natl Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Qufu Normal Univ, Sch Math Sci, Qufu 273165, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Delay differential equations; Lyapunov functionals; Matrix inequality; Exponential stability; GLOBAL ASYMPTOTIC STABILITY; TIME DELAYS; ROBUST STABILITY;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new simple sufficient condition is presented for the exponential stability of stochastic cellular neural networks with discrete delays. The condition contains and improves some of the previous results in the earlier references. These sufficient conditions only including those governing parameters of SDCNNs can be easily checked by simple algebraic methods. Finally, one example is given to demonstrate that the proposed criteria are useful and effective.
引用
收藏
页码:1 / 10
页数:10
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