Finite-time synchronization of memristive neural networks with parameter uncertainties via aperiodically intermittent adjustment

被引：21

作者：

Zhang, Shuai ^{[2
]}

Yang, Yongqing ^{[1
]}

Sui, Xin ^{[2
]}

Xu, Xianyu ^{[1
]}

机构：

[1] Jiangnan Univ, Sch Sci, Wuxi 214122, Jiangsu, Peoples R China

[2] Jiangnan Univ, Sch IoT Engn, Wuxi 214122, Jiangsu, Peoples R China

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2019年 / 534卷

关键词：

Finite-time; Synchronization; Memristive neural network; Parameter uncertainties; Aperiodically intermittent; 2ND-ORDER MULTIAGENT SYSTEMS; GLOBAL EXPONENTIAL SYNCHRONIZATION; DELAYED NONLINEAR DYNAMICS; VARYING DELAYS; LIMIT-CYCLES; MIXED DELAYS; PINNING SYNCHRONIZATION; COMPLEX NETWORKS; STABILITY; BIFURCATION;

D O I：

10.1016/j.physa.2019.122258

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

This paper is concerned with finite-time synchronization of memristive neural networks with parameter uncertainties by using aperiodically intermittent strategy. Based on the existed finite-time theory of intermittent strategy, a finite-time aperiodically intermittent stability lemma is proposed. In the sense of Filippov's framework, an appropriate Lyapunov functional is constructed to realize the finite-time synchronization by designing a appropriate aperiodically intermittent controller. The derived sufficient conditions can effectively eliminate the influence of parameter uncertainties and make the systems achieve finite-time synchronization. Finally, a numerical simulation example is given to demonstrate the validity of the sufficient conditions. (C) 2019 Elsevier B.V. All rights reserved.

引用

页数：16

共 50 条

[1] Finite-Time and Fixed-Time Synchronization of Delayed Memristive Neural Networks via Adaptive Aperiodically Intermittent Adjustment Strategy
Cheng, Liyan
Tang, Fangcheng
Shi, Xinli
Chen, Xiangyong
Qiu, Jianlong
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (11) : 8516 - 8530
[2] Aperiodically intermittent strategy for finite-time synchronization of delayed neural networks
Liu, Mei
Jiang, Haijun
Hu, Cheng
NEUROCOMPUTING, 2018, 310 : 1 - 9
[3] Finite-Time Synchronization of Memristive Neural Networks with Uncertainties and External Disturbances
Wang, S. -f.
NEURAL PROCESSING LETTERS, 2024, 56 (06)
[4] Finite-time synchronization of delayed dynamical networks via aperiodically intermittent control
Liu, Mei
Jiang, Haijun
Hu, Cheng
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (13): : 5374 - 5397
[5] Finite-time synchronization of delayed complex dynamic networks via aperiodically intermittent control
Jing, Taiyan
Zhang, Daoyuan
Mei, Jun
Fan, Yuling
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (10): : 5464 - 5484
[6] Synchronization for Fuzzy Models of Memristive Stochastic Neural Networks via Aperiodically Intermittent Control
Chen, Siya
Feng, Jianwen
Zhao, Yi
PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 6056 - 6061
[7] Finite-time synchronization of fractional-order memristive neural networks via feedback and periodically intermittent control
Hui, Meng
Wei, Chen
Zhang, Jiao
Iu, Herbert Ho-Ching
Yao, Rui
Bai, Lin
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2023, 116
[8] Finite-Time Lag Synchronization for Memristive Mixed Delays Neural Networks with Parameter Mismatch
Lingzhong Zhang
Yongqing Yang
Fei Wang
Xin Sui
Neural Processing Letters, 2018, 47 : 365 - 389
[9] Finite-Time Lag Synchronization for Memristive Mixed Delays Neural Networks with Parameter Mismatch
Zhang, Lingzhong
Yang, Yongqing
Wang, Fei
Sui, Xin
NEURAL PROCESSING LETTERS, 2018, 47 (02) : 365 - 389
[10] Aperiodically Intermittent Control for Finite-Time Synchronization of Delayed Complex Dynamical Networks
Zhang, Weihai
Liu, Hongping
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 1391 - 1396

← 1 2 3 4 5 →