GLOBAL EXPONENTIAL STABILITY OF HOPFIELD NEURAL NETWORKS WITH VARIABLE DELAYS AND IMPULSIVE EFFECTS

A class of Hopfield neural network with time-varying delays and impulsive effects is concerned. By applying the piecewise continuous vector Lyapunov function some sufficient conditions were obtained to ensure the global exponential stability of impulsive delay neural networks. An example and its sim...

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Bibliographic Details
Published in:Applied mathematics and mechanics 2006-11, Vol.27 (11), p.1517-1522
Main Author: 杨志春 徐道义
Format: Article
Language:English
Subjects:
Computer simulation
Delay
Lyapunov functions
Mathematical analysis
Neural networks
Stability
Vectors (mathematics)
神经系统网络
稳定性
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Summary:A class of Hopfield neural network with time-varying delays and impulsive effects is concerned. By applying the piecewise continuous vector Lyapunov function some sufficient conditions were obtained to ensure the global exponential stability of impulsive delay neural networks. An example and its simulation are given to illustrate the effectiveness of the results.
ISSN:0253-4827
1573-2754
DOI:10.1007/s10483-006-1109-1