Finite-time projective synchronization of memristor-based neural networks with leakage and time-varying delays
文献类型： 外文期刊
作者： Qin, Xiaoli 1 ; Wang, Cong 2 ; Li, Lixiang 3 ; Peng, Haipeng 3 ; Yang, Yixian 3 ; Ye, Lu 4 ;
作者机构： 1.Beijing Univ Posts & Telecommun, Sch Software Engn, Beijing 100876, Peoples R China
2.Beijing Univ Posts & Telecommun, Key Lab Trustworthy Distributed Comp & Serv, Minist Educ, Beijing 100876, Peoples R China
3.Beijing Univ Posts & Telecommun, Natl Engn Lab Disaster Backup & Recovery, Beijing 100876, Peoples R China
4.Chinese Acad Trop Agr Sci, Inst Sci & Tech Informat, Haikou 571101, Hainan, Peoples R China
关键词： Finite-time synchronization; Memristor-based neural networks(MNNs); Leakage delay; Projective synchronization
期刊名称：PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS （ 影响因子：3.263； 五年影响因子：2.866 ）
ISSN： 0378-4371
年卷期： 2019 年 531 卷
页码：
收录情况： SCI
摘要： This paper is concerned with the finite-time projective synchronization problem of memristor-based neural networks(MNNs) with leakage and time-varying delays. The finite-time modified projective synchronization and function projective synchronization theorems are proposed, and the approach of Lyapunov stability and two different finite-time synchronization methods are adopted in the proof processes. Based on time-delay correlation and irrelevant problem, two different controllers are designed, and several stability conditions are presented to ensure that the drive response systems achieve the finite-time synchronization with arbitrary continuous bounded functions. Meanwhile, several corollaries about the special cases of finite-time projective synchronization are given along with the theorems. Finally, two numerical simulations are carried out to illustrate the effectiveness and verify our results. (C) 2019 Elsevier B.V. All rights reserved.
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