Exponential Stability of Delayed Neural Networks with Impulses

This paper investigates the stability of a class of delayed neural networks with impulses. By means of Lyapunov direct method, the new sufficient conditions for exponential stability of the systems are derived.

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Bibliographic Details
Main Authors: Jin-Xiang Yang, Shou-Ming Zhong, Jian-Cheng Song
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Computer science
Delay effects
Differential equations
Educational institutions
Exponential stability
Hopfield neural networks
impulsive
Neural networks
Recurrent neural networks
Stability criteria
Sufficient conditions
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Description
Summary:This paper investigates the stability of a class of delayed neural networks with impulses. By means of Lyapunov direct method, the new sufficient conditions for exponential stability of the systems are derived.
DOI:10.1109/ICACIA.2008.4770015