Finite-time sampled-data synchronization for uncertain neutral-type semi-Markovian jump neural networks with mixed time-varying delays

被引：18

作者：

Wang, Yao ^{[1
]}

Guo, Jun ^{[1
]}

Liu, Guobao ^{[2
]}

Lu, Junwei ^{[2
]}

Li, Fangyuan ^{[3
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China

[2] Nanjing Normal Univ, Sch Elect & Automat Engn, Nanjing 210023, Peoples R China

[3] Nanjing Vocat Coll Informat Technol, Sch Elect & Informat, Nanjing 210046, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2021年 / 403卷

基金：

中国国家自然科学基金;

关键词：

Finite-time analysis; Semi-Markovian jump; Sampled-data control; Synchronization; Neutral-type neural networks; Mixed time delays; EXPONENTIAL SYNCHRONIZATION; INFINITY SYNCHRONIZATION; TRANSITION-PROBABILITIES; INEQUALITY APPLICATION; STABILITY ANALYSIS; STATE ESTIMATION; SYSTEMS SUBJECT; DISCRETE;

D O I：

10.1016/j.amc.2021.126197

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper addresses the finite-time synchronization problem for neutral-type semi-Markovian jump neural networks subject to random occurred uncertainties by sampled-data control approach. In order to deal with the influence of leakage delay and additive time delays on neutral-type neural networks, an appropriate Lyapunov-Krasovskii functional is employed. Some sufficient conditions are presented to guarantee the stochastic finite-time synchronization of the master system and slave system with an L-2 - L-infinity performance level. In terms of linear matrix inequalities, the sampled-data controller gains are obtained. Two numerical examples are provided to demonstrate the effectiveness of our proposed method. (C) 2021 Elsevier Inc. All rights reserved.

引用

页数：13

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