Periodic Solution for Neutral-Type Neural Networks in Critical Case

被引：8

作者：

Du, Bo ^{[1
,2
]}

Lu, Shiping ^{[3
]}

Liu, Yurong ^{[2
]}

机构：

[1] Huaiyin Normal Univ, Dept Math, Huaian 223300, Jiangsu, Peoples R China

[2] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China

[3] NUIST, Coll Math & Phys, Nanjing 210044, Jiangsu, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2016年 / 44卷 / 03期

关键词：

Neural networks; Neutral-type; Periodic solution; Critical case; FUNCTIONAL-DIFFERENTIAL EQUATION; ASYMPTOTIC STABILITY; TIME DELAYS; SYSTEMS;

D O I：

10.1007/s11063-015-9493-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A generalized neutral-type neural networks in critical case is studied. Some existence and asymptotic behavior results of periodic solution to the neutral-type neural networks in critical case are obtained by continuation theorem of coincidence degree theory and some analysis techniques. Finally, an example is given to show the effectiveness of the results in this paper.

引用

页码：765 / 777

页数：13

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