Global Stability of Almost Periodic Solution of a Class of Neutral-Type BAM Neural Networks

被引：1

作者：

Pan, Tetie ^{[1
]}

Shi, Bao ^{[1
]}

Yuan, Jian ^{[1
]}

机构：

[1] Naval Aeronaut & Astronaut Univ, Inst Syst Sci & Math, Yantai 264001, Shandong, Peoples R China

来源：

ABSTRACT AND APPLIED ANALYSIS | 2012年

关键词：

EXPONENTIAL STABILITY; EXISTENCE; UNIQUENESS; DISCRETE; DELAYS;

D O I：

10.1155/2012/482584

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A class of BAM neural networks with variable coefficients and neutral delays are investigated. By employing fixed-point theorem, the exponential dichotomy, and differential inequality techniques, we obtain some sufficient conditions to insure the existence and globally exponential stability of almost periodic solution. This is the first time to investigate the almost periodic solution of the BAM neutral neural network and the results of this paper are new, and they extend previously known results.

引用

页数：18

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