具有变时滞的神经型Hopfield神经网络的全局吸引子研究

数学物理学报 ›› 2019, Vol. 39 ›› Issue (4): 823-831.

具有变时滞的神经型Hopfield神经网络的全局吸引子研究

周庆华¹,万立^2,*(),刘杰²

¹ 肇庆学院数学与统计学院广东肇庆 526061
² 武汉纺织大学数学与计算机学院武汉 430073

收稿日期:2018-04-01 出版日期:2019-08-26 发布日期:2019-09-11
通讯作者: 万立 E-mail:wanlinju@aliyun.com
基金资助:
国家自然科学基金(11501499);国家自然科学基金(61573011);国家自然科学基金(11301403);国家自然科学基金(61304022);国家自然科学基金(11271295);广东省自然科学基金(2015A030313707)

Global Attracting Set for Neutral Type Hopfield Neural Networks with Time-Varying Delays

Qinghua Zhou¹,Li Wan^2,*(),Jie Liu²

¹ School of Mathematics and Statistics, Zhaoqing University, Guangdong Zhaoqing 526061
² College of Mathematics and Computer Sciences, Wuhan Textile University, Wuhan 430073

Received:2018-04-01 Online:2019-08-26 Published:2019-09-11
Contact: Li Wan E-mail:wanlinju@aliyun.com
Supported by:
the NSFC(11501499);the NSFC(61573011);the NSFC(11301403);the NSFC(61304022);the NSFC(11271295);the Natural Science Foundation of Guangdong Province(2015A030313707)

摘要/Abstract

摘要：

该文探讨了一类具有变时滞的非线性及非自治的神经型Hopfield神经网络的渐近性质.利用非负矩阵的性质和矩阵不等式，得到了保证该系统全局吸引集存在和Lagrange稳定性的充分条件.最后，给出一个例子说明理论的有效性.

关键词: 神经型Hopfield神经网络, 变时滞, Lagrange稳定, 全局吸引集, 积分不等式

Abstract:

This paper deals with the asymptotic properties of a class of nonlinear and nonautonomous neutral type Hopfield neural networks with time-varying delays. By applying the property of nonnegative matrix and an integral inequality, some sufficient conditions are derived to ensure the existence of the global attracting set and the stability in a Lagrange sense for the considered system. Finally, an example is given to demonstrate the effectiveness of our theoretical result.

Key words: Neutral-type Hopfield neural networks, Time-varying delays, Lagrange stability, Global attracting set, Integral inequality

中图分类号:

O193

周庆华,万立,刘杰. 具有变时滞的神经型Hopfield神经网络的全局吸引子研究[J]. 数学物理学报, 2019, 39(4): 823-831.

Qinghua Zhou,Li Wan,Jie Liu. Global Attracting Set for Neutral Type Hopfield Neural Networks with Time-Varying Delays[J]. Acta mathematica scientia,Series A, 2019, 39(4): 823-831.

图/表 1

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