摘要
讨论了一类含时滞和脉冲的双向联想记忆神经网络模型的鲁棒渐近稳定性.通过构造恰当的Lyapunov泛函和使用线性矩阵不等式技巧,获得了该模型全局鲁棒一致渐近稳定的充分条件.通过2个例子说明了结论的有效性.
In this paper, the global robust uniformly asymptotic stability of the equilibrium point for a class of bidirectional associatire memory neural networks with time delays and impulses is studied. New delay independent sufficient conditions are obtained for the global robust uniformly asymptotic stability of bidirectional associative memory neural networks with time delays and impulses by employing suitable Lyapunov funetionals and linear matrix inequality approach. Two examples are given to demonstrate the applicability and effectiveness.
出处
《四川师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第2期177-184,共8页
Journal of Sichuan Normal University（Natural Science）
基金
国家自然科学基金(11271270)
四川省应用基础研究(2009JY0066)
四川省教育厅自然科学重点基金(10ZA125)
高等学科博士点学科专项科研基金(20105134110001)资助项目
关键词
时滞
脉冲
双向联想记忆神经网络模型
全局鲁棒一致渐近稳定性
time delays
impulses
bidirectional associative memory neural networks
global robust uniformly asymptotic stability
