Exponential stability of a class of impulsive neural networks with variable delays

The main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of impulsive neural networks with time-varying delays. Without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, combining Hal...

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Bibliographic Details
Main Authors: Jianfu Yang, Fengjian Yang, Jicheng Tao, Wei Li, Dongqing Wu
Format: Conference Proceeding
Language:English
Subjects:
Asymptotic stability
Automation
Cellular neural networks
Delay effects
Globally exponential stability
Hydrogen
Impulse
Lyapunov function
Lyapunov method
Neural networks
Neurons
Stability criteria
Sufficient conditions
Time-varying delays
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Summary:The main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of impulsive neural networks with time-varying delays. Without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, the sufficient conditions for globally exponential stability of neural networks are obtained.
ISSN:2161-8151
2161-816X
DOI:10.1109/ICAL.2009.5262749