Different Control Strategies for Fixed-Time Synchronization of Inertial Memristive Neural Networks

被引：4

作者：

Zhang, Lingzhong ^{[1
]}

Yang, Yongqing ^{[2
]}

机构：

[1] Changshu Inst Technol, Sch Elect Engn & Automat, Changshu, Jiangsu, Peoples R China

[2] Jiangnan Univ, Wuxi Engn Res Ctr Biocomp, Sch Sci, Wuxi 214122, Jiangsu, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2022年 / 54卷 / 05期

基金：

中国博士后科学基金;

关键词：

Memristor; Fixed-time; Impulse effect; Adaptive; Synchronization; IMPULSIVE CONTROL; VARYING DELAYS; EXPONENTIAL STABILITY; FINITE-TIME;

D O I：

10.1007/s11063-022-10779-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this brief, fixed-time synchronization problem for inertial memristive neural networks (IMNNs) with impulsive and adaptive control is investigated. Instead of modeling the memristor as a right-hand discontinuous system, memristor is regarded as an uncertain continuous time-varying parameter, memristive neural networks (MNNs) is modeled as a neural network (NNs) with polytopic uncertainty and time varying parameters. By establishing comparison system, the criteria are established for synchronization of IMNNs in a setting time with impulsive and adaptive control input. Based on convex combination method, the influence of different impulsive effects on synchronization behavior of the system is analyzed by dividing the impulsive interval. Finally, numerical examples are given for illustration.

引用

页码：3657 / 3678

页数：22

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