Sampled-data synchronization criteria for Markovian jumping neural networks with additive time-varying delays using new techniques

被引：11

作者：

Wu, Tao ^{[1
,2
]}

Cao, Jinde ^{[1
,2
,3
]}

Xiong, Lianglin ^{[4
]}

Zhang, Haiyang ^{[4
]}

Shu, Jinlong ^{[5
]}

机构：

[1] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China

[2] Southeast Univ, Res Ctr Complex Syst & Network Sci, Nanjing 210096, Peoples R China

[3] Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea

[4] Yunnan Minzu Univ, Sch Math & Comp Sci, Kunming 650500, Yunnan, Peoples R China

[5] Shaanxi Normal Univ, Sch Math & Informat Sci, Xian 710062, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2022年 / 413卷

基金：

中国国家自然科学基金;

关键词：

Markovian jumping neural networks; Additive time-varying delays; Sampled-data control; Synchronization; EXPONENTIAL SYNCHRONIZATION; LINEAR-SYSTEMS; NEUTRAL-TYPE; TRANSITION-PROBABILITIES; COMPLEX NETWORKS; STABILITY; STABILIZATION; COMMUNICATION; PARAMETERS;

D O I：

10.1016/j.amc.2021.126604

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper investigates the sampled-data synchronization issue of Markovian jumping neural networks with additive time-varying delays. Firstly, a ternary quadratic function negative-determination condition and the bilateral sampled-interval-related Lyapunov functional (BSIRLF) approach are proposed. Based on the developed two novel approaches, some new criteria based on the linear matrix inequalities (LMIs) are established to guarantee the drive-response stochastic sampled-data synchronization of Markovian jumping neural networks with additive time-varying delays. Meanwhile, the corresponding sampled-data controller gains are designed under the larger sampling interval. In the end, the availability and merits of the developed approaches are displayed via two simulative examples. (C) 2021 Elsevier Inc. All rights reserved.

引用

页数：21

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