Global asymptotic stability of Hopfield neural network involving distributed delays

2004 ◽  
Vol 17 (1) ◽  
pp. 47-53 ◽  
Author(s):  
Hongyong Zhao
Keyword(s):  
Neural Network ◽  
Asymptotic Stability ◽  
Global Asymptotic Stability ◽  
Hopfield Neural Network ◽  
Distributed Delays

ON THE GLOBAL ASYMPTOTIC STABILITY ANALYSIS OF DELAYED NEURAL NETWORKS

2005 ◽  
Vol 15 (12) ◽  
pp. 4019-4025 ◽  
Author(s):  
ZHAOHUI YUAN ◽  
DEWEN HU ◽  
LIHONG HUANG ◽  
GUOHUA DONG
Keyword(s):  
Neural Network ◽  
Asymptotic Stability ◽  
Global Asymptotic Stability ◽  
Hopfield Neural Network ◽  
Cellular Neural Network ◽  
Functional Method ◽  
Activation Functions ◽  
Delayed Neural Networks ◽  
System Parameters ◽  
Lyapunov Functional Method

In this paper, the problem of the global asymptotic stability (GAS) of a class of delayed neural network is investigated. Under the generalization of dropping the boundedness and differentiability hypotheses for activation functions, using some existing results for the existence and uniqueness of the equilibrium point, we obtain a couple of general results concerning GAS by means of Lyapunov functional method without the assumption of symmetry of interconnection matrix. Our results improve and extend some previous works of other researchers. Moreover, our conditions are presented in terms of system parameters, which have leading significance in designs and applications of GAS for Hopfield neural network (HNNs) and delayed cellular neural network (DCNNs).

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