Stability analysis of delayed cellular neural networks with and without noise perturbation

被引:1
|
作者
Zhang Xue-juan [2 ]
Wang Guan-xiang [1 ]
Liu Hua [3 ]
机构
[1] Peking Univ, Sch Math Sci, LMAM, Beijing 100871, Peoples R China
[2] Shaoxing Univ, Dept Math, Shaoxing 312000, Zhejiang, Peoples R China
[3] Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
delayed cellular neural networks; global exponential stability; external; internal noise; O175; O211; 92B20; 92C20; 37H15;
D O I
10.1007/s10483-008-1104-x
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The stability of a class of delayed cellular neural networks (DCNN) with or without noise perturbation is studied. After presenting a simple and easily checkable condition for the global exponential stability of a deterministic system, we further investigate the case with noise perturbation. When DCNN is perturbed by external noise, the system is globally stable. An important fact is that, when the system is perturbed by internal noise, it is globally exponentially stable only if the total noise strength is within a certain bound. This is significant since the stochastic resonance phenomena have been found to exist in many nonlinear systems.
引用
收藏
页码:1427 / 1438
页数:12
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