Stability conditions concerning neutral-type BAM neural networks with infinite distributed delay

被引：4
|
作者：
Liu, Guo-Quan [1 ]
Zhou, Shu-Min [1 ]
Li, Yue-Zhong [1 ]
Cai, Tong-Chen [1 ]
机构：
[1] East China Univ Technol, Sch Mech & Elect Engn, Jiangxi Prov Engn Res Ctr New Energy Technol & Eq, Nanchang 330013, Jiangxi, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2021年 / 98卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Global stability; neutral-type; Lyapunov functional method; BAM neural networks; infinite distributed delays; GLOBAL EXPONENTIAL STABILITY; TIME-VARYING DELAYS; ASYMPTOTIC STABILITY; SYNCHRONIZATION; BIFURCATION;
D O I：
10.1080/00207160.2020.1759043
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper presents a class model for neutral-type bidirectional associative memory (BAM) neural networks (NNS) with infinite distributed delay. The model extends and improves some recent works for BAM-NNS. Based on the Lyapunov-Krasovskii functional (LKF) theory, the linear matrix inequality (LMI) method and some analysis techniques, the novel stability criteria for such model are obtained. Four numerical examples prove the validity and less conservativeness of the proposed criteria. The developed results are helpful to design of an actual system.
引用
收藏
页码：502 / 516
页数：15
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