Title of article :
GLOBAL EXPONENTIAL STABILITY FOR REACTION–DIFFUSION RECURRENT NEURAL NETWORKS WITH MULTIPLE TIME-VARYING DELAYS
Author/Authors :
Lou, Xuyang Jiangnan University - College of Communication and Control Engineering, China , Cui, Baotong Jiangnan University - College of Communication and Control Engineering, China
Abstract :
In this paper, we consider the problem of exponential stability for recurrent neural networks with multiple time-varying delays and reaction–diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functionals, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis
Keywords :
Global exponential stability , reaction , diffusion terms , neural networks , multiple time , varying delays , Lyapunov functional
Journal title :
The Arabian Journal for Science and Engineering
Journal title :
The Arabian Journal for Science and Engineering
