STABILITY ANALYSIS OF A CLASS OF GENERAL PERIODIC NEURAL NETWORKS WITH DELAYS AND IMPULSES

被引：4

作者：

Zhao, Yong ^{[1
]}

Xia, Yonghui ^{[2
]}

Lu, Qishao ^{[1
]}

机构：

[1] Beihang Univ, Dept Dynam & Control, Beijing 100191, Peoples R China

[2] Zhejiang Normal Univ, Dept Math, Jinhua 210034, Peoples R China

来源：

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2009年 / 19卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Neural network; periodic solution; delay; impulse; global exponential stability; GLOBAL EXPONENTIAL STABILITY; TIME-VARYING DELAYS; DIFFERENTIAL-EQUATIONS; VARIABLE-COEFFICIENTS; ASYMPTOTIC STABILITY; DISTRIBUTED DELAYS; DYNAMICS MODEL; OPTIMIZATION; EXISTENCE; OSCILLATION;

D O I：

10.1142/S012906570900204X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Based on the inequality analysis, matrix theory and spectral theory, a class of general periodic neural networks with delays and impulses is studied. Some sufficient conditions are established for the existence and globally exponential stability of a unique periodic solution. Furthermore, the results are applied to some typical impulsive neural network systems as special cases, with a real-life example to show feasibility of our results.

引用

页码：375 / 386

页数：12

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