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Finite-Time and Fixed-Time Synchronization of inertial neural networks with Mixed Delays

Journal of Systems Science & Complexity 2021年第1期34卷 206-235页

作者： CHAOUKI Aouiti EL ABED Assali University of Carthage Faculty of Sciences of BizertaDepartment of MathematicsResearch Units of Mathematics and Applications UR13ES477021 ZarzounaBizertaTunisia

This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities,some new and effective criteria are obtained for ensuring the finite-time synchronization. Finally, three numerical examples are also given at the end of this paper to show the effectiveness of the results.

关键词： Finite-time synchronization fixed-time synchronization inertial neural networks infinitetime distributed delays time-varying delays

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Chaotic Lag Synchronization of a Class of inertial neural networks with Unbounded Distributed Delays

Chaotic Lag Synchronization of a Class of Inertial Neural Ne...

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第32届中国控制与决策会议

作者： Changqing Long Guodong Zhang School of Mathematics and Statistics South-Central University For Nationalities

This article investigates the chaotic exponential lag synchronization of a class of inertial neural networks（INNs） with unbounded distributed delays. Firstly, the second-order INNs is transformed into the first-order differential equation through a suitable variable transformation. Secondly, the sufficient exponential lag synchronization conditions are established for INNs with unbounded distributed delays via the feedback control theory and Lyapunov stability *** last, the feasibility of the derived results are illustrated by numerical examples.

关键词： Lag synchronization inertial neural networks Unbounded distributed delays Lyapunov stability theory

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Synchronization of fractional order memristor-based inertial neural networks with time delay

Synchronization of fractional order memristor-based inertial...

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第32届中国控制与决策会议

作者： Xingyu Yang Junguo Lu Department of Automation Shanghai Jiao Tong University

In this paper,the synchronization problem of fractional order memristor-based inertial neural networks are *** facilitate the analysis,the set-valued mapping theory is applied to the discontinuity problem caused by *** fractional order memristive inertial neural networks have two fractional derivative terms,it is hard to *** solve this problem,a special feedback controller is designed in this paper to offset the fractional derivative term between 0 and 1 and the stability theory of the fractional autonomous system is used to analyze the fractional derivative term between 1 and *** some sufficient conditions for the synchronization of fractional order memristive inertial neural networks are ***,the effectiveness of the conclusion is verified by an example.

关键词： Synchronization Fractional Order Memritsor inertial neural networks

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Impulsive synchronization control of delayed inertial BAM neural networks with reaction–diffusion terms

Impulsive synchronization control of delayed inertial BAM ne...

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第37届中国控制会议

作者： Weiyuan Zhang Zhenhua Wang Leilei Zhang Institute of Nonlinear Science Xianyang Normal University School of Science Xidian University

In the paper,a seconded-order delay-differential equation modelling an inertial bidirectional associative memory neural network with reaction-diffusion terms is *** suitable variable substitution,the considered systems-order differential *** state global exponential synchronization of two identical such system is derived by constructing a suitable Lyapunov functional,utilizing impulsive control and some inequality techniques.A global exponential synchronization criterion is presented in terms of algebraic inequalities.A numerical example is provided to demonstrate the effectiveness of the proposed results.

关键词： inertial neural networks Reaction–diffusion delays Global exponential synchronization Lyapunov functional

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New results on impulsive type inertial bidirectional associative memory neural networks

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Frontiers of Information Technology & Electronic Engineering 2020年第2期21卷 324-339页

作者： Chaouki AOUITI Mahjouba Ben REZEG Yang CAO Department of Mathematics the University of CarthageXarzouna 7021BizertaTunisia School of Cyber Science and Engineering Southeast UniversityNanjing 211189China Department of Mechanical Engineering the University of Hong KongPokfulamHong KongChina

This paper is concerned with inertial bidirectional associative memory neural networks with mixed delays and impulsive *** and practical conditions are given to study the existence,uniqueness,and global exponential stability of anti-periodic solutions for the suggested *** use differential inequality techniques to prove our main ***,we give an illustrative example to demonstrate the effectiveness of our new results.

关键词： inertial neural networks Anti-periodic solutions Global exponential stability Impulsive effect Time-varying delay Bidirectional associative memory

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