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对时滞BAM神经网络脉冲上界的估计
引用本文:王建军,王慧.对时滞BAM神经网络脉冲上界的估计[J].重庆交通学院学报,2009(3).
作者姓名:王建军  王慧
作者单位:乐山师范学院计算机系;乐山师范学院数学系;
基金项目:中国博士后科学基金(20080431274)
摘    要:研究了时滞双向联想神经网络的指数稳定性,集中讨论了脉冲对指数稳定性的影响。结果显示,若非脉冲DBAM系统全局指数稳定,即使状态在脉冲时刻被放大到某一较大范围,相应的脉冲系统也能保持其稳定特性。根据非脉冲系统的指数收敛度,对保持系统指数稳定的脉冲上界和脉冲间隔进行了估计。

关 键 词:双向联想神经网络(BAM神经网络)  指数稳定性  时滞  脉冲稳定性  

Estimate of Pulse Upper Bound in Time-Delay BAM Neural Networks
WANG Jian-jun,WANG Hui.Estimate of Pulse Upper Bound in Time-Delay BAM Neural Networks[J].Journal of Chongqing Jiaotong University,2009(3).
Authors:WANG Jian-jun  WANG Hui
Institution:WANG Jian-jun1,WANG Hui2(1.Department of Computer,Leshan Normal University,Sichuan Leshan 614004,China,2.Department of Mathematics,China)
Abstract:The exponential stability of delayed bidirectional associative memory neural networks(DBAM neural networks) is studied and the influence of pulse on exponential stability is focused.The result shows that if the whole exponent of non-pulse DBAM is stable,the corresponding pulse system can remain its stability,even if the state are magnified to a larger scale at the pulse instant.Furthermore,the pulse upper bound and pulse interval which can keep the exponents of the system stable is estimated,according to th...
Keywords:delayed bidirectional associative memory neural networks(DBAM neural networks)  exponential stability  time-delay  pulse stability  
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