Stability analysis for periodic solution of BAM neural networks with discontinuous neuron activations and impulses

被引:56
|
作者
Wu, Huaiqin [1 ]
Shan, Caihong [1 ]
机构
[1] Yanshan Univ, Dept Math, Qinhuangdao 066001, Peoples R China
关键词
Neural networks; Global exponential stability; Neuron activation functions; Impulses; Periodic solution; Differential inclusions; GLOBAL EXPONENTIAL STABILITY; TIME-VARYING DELAYS; CONVERGENCE; EXISTENCE;
D O I
10.1016/j.apm.2008.07.022
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, we present a general class of BAM neural networks with discontinuous neuron activations and impulses. By using the fixed point theorem in differential inclusions theory, we investigate the existence of periodic solution for this neural network. By constructing the suitable Lyapunov function, we give a sufficient condition which ensures the uniqueness and global exponential stability of the periodic solution. The results of this paper show that the Forti's conjecture is true for BAM neural networks with discontinuous neuron activations and impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper. (C) 2008 Elsevier Inc. All rights reserved.
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页码:2564 / 2574
页数:11
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