Exponential Stability Analysis of Cohen-Grossberg Neural Networks with Time-varying Delays

In this paper, we study Cohen-Grossberg neural networks （CGNN） with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our...

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Bibliographic Details
Published in:Acta Mathematicae Applicatae Sinica 2012, Vol.28 (1), p.181-192
Main Authors: Meng, Yi-min, Huang, Li-hong, Yuan, Zhao-hui
Format: Article
Language:English
Subjects:
Applications of Mathematics
Cohen-Grossberg神经网络
Math Applications in Computer Science
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Theoretical
不等式
充分条件
全局指数稳定
存在唯一性
时变时滞
稳定性分析
重合度
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Summary:In this paper, we study Cohen-Grossberg neural networks （CGNN） with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our results complement previously known results.
ISSN:0168-9673
1618-3932
DOI:10.1007/s10255-012-0133-y