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Journal of Systems Science & Complexity 2024年第1期37卷 294-317页

作者： WU Wenhuang GUO Lulu CHEN Hong Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

This paper is devoted to event-triggered synchronization of delayed memristive neural networks with H∞and passivity *** aim is to guarantee the exponential synchronization and mixed H∞and passivity control for memristive neural networks by using event-triggered ***,a switching system is constructed under the event-triggered control ***,by adopting a piece-wise Lyapunov functional,a sufficient condition is established for the exponential synchronization and mixed H_(∞)and passivity ***,an event-triggered controller design scheme is proposed using matrix decoupling ***,the effectiveness of the designed controller is exemplified by a numerical example.

关键词： Event-triggered control exponential synchronization memristive neural networks time delays.

Event-triggered hybrid impulsive control for synchronization of memristive neural networks

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Science China(Information Sciences) 2020年第5期63卷 75-86页

作者： Yijun ZHANG Yuangui BAO Automation School Nanjing University of Science and Technology

This paper is concerned with the complete synchronization of memristive neural networks(MNNs) with time-varying delays. An event-triggered hybrid state feedback and impulsive controller is designed to save the limited system communication resources, and parameter mismatch is considered in the control design process. Based on the Lyapunov functional approach and the comparison principle for impulsive systems, a sufficient synchronization criterion is developed to derive the master MNN and response ***, under the event-triggered mechanism there exists a positive lower bound for inter-execution time, which implies the avoidance of Zeno behavior. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization design methods.

关键词： event-triggered synchronization memristive neural networks impulsive control Zeno behavior

Synchronization of Stochastic memristive neural networks with Retarded and Advanced Argument

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Journal of Intelligent Learning Systems and Applications 2021年第1期13卷 1-14页

作者： Renxiang Xian School of Mathematics and Statistics Hubei Normal University Huangshi China

In this paper, we discuss the driving-response synchronization problem for two memristive neural networks with retarded and advanced arguments under the condition of additional noise. The control law is related to the linear time-delay feedback term, and the discontinuous feedback term. Moreover, the random different equation is used to prove the stability of this theory. At the end, the simulation results verify the correctness of the theoretical results.

关键词： Synchronization memristive neural networks Random Disturbance Time-Delay Feedback Adaptive Control Retarded and Advanced System

Memory Analysis for Memristors and memristive Recurrent neural networks

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IEEE/CAA Journal of Automatica Sinica 2020年第1期7卷 96-105页

作者： Gang Bao Yide Zhang Zhigang Zeng Key Laboratory of Cascaded Hydropower Stations Operation and Control Electrical Engineering and New EnergyChina Three Gorges UniversityYichang 443002and Hubei Key Laboratory of Applied Mathematics(Hubei University)Wuhan 430074China Department of Medical Engineering California Institute of TechnologyPasadenaCalifornia 91125 USA School of Artificial Intelligence and Automation Huazhong University of Science and Technologyand also with the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of ChinaWuhan 430074China

Traditional recurrent neural networks are composed of capacitors, inductors, resistors, and operational *** neural networks are constructed by replacing resistors with memristors. This paper focuses on the memory analysis,i.e. the initial value computation, of memristors. Firstly, we present the memory analysis for a single memristor based on memristors’ mathematical models with linear and nonlinear ***, we present the memory analysis for two memristors in series and parallel. Thirdly, we point out the difference between traditional neural networks and those that are memristive. Based on the current and voltage relationship of memristors, we use mathematical analysis and SPICE simulations to demonstrate the validity of our methods.

关键词： Dopant drift memory memristive neural networks memristor

Robust Finite-Time Passivity and Synchronization of Coupled Complex-Valued memristive neural networks with Parameter Uncertainty

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Robust Finite-Time Passivity and Synchronization of Coupled ...

第40届中国控制会议

作者： Fang Wu Yanli Huang School of Computer Science and Technology Tiangong University

This paper deals with the robust finite-time passivity（RFTP） and robust finite-time synchronization（RFTS） problems for coupled complex-valued memristive neural networks（CCVMNNs） with parameter uncertainty. By virtue of constructing a suitable controller combined with employing Lyapunov functional method, a sufficient RFTP condition is provided for the considered CCVMNNs. Furthermore, a RFTS criterion under the condition that the CCVMNNs achieves RFTP is also *** last, a numerical example with simulation substantiates the correctness and validity of the acquired results.

关键词： robust finite-time passivity robust finite-time synchronization memristive neural networks complex-valued neural networks

Exponential Synchronization of Stochastic memristive neural networks with Delays Using Periodically Intermittent Observation Feedback Control

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Exponential Synchronization of Stochastic Memristive Neural ...

第32届中国控制与决策会议

作者： Jiayi Cai Jianwen Feng Yi Zhao College of Mathematics and Statistic Shenzhen University

This paper focuses on the mean-square exponential synchronization problem for the stochastic memristive neural networks with delays through periodic intermittent observation feedback control（PIOFC）.The goal of this issue is to design a discrete observation controller that tolerates the stochastic *** constructing a Lyapunov function,we establish a sufficient condition to guarantee the mean-square synchronization of the *** addition,some criteria are applied to ensure that the drive system can be synchronized to the response ***,some simulation examples are raised to demonstrate the effectiveness of our proposed scheme.

关键词： memristive neural networks delays periodically intermittent observation feedback control synchronization

Finite-Time Anti-Synchronization Control of memristive neural networks with Time Delays

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Finite-Time Anti-Synchronization Control of Memristive Neura...

第三十九届中国控制会议

作者： Jie Wu Leimin Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the finite-time anti-synchronization problem of memristive neural networks（MNNs） with time-varying delays. First, a delayed-feedback controller is constructed to realize the anti-synchronization. Then, by employing appropriate Lyapunov-Krasovskii functional and the designed controller, new sufficient criteria are derived for the finite-time anti-synchronization of MNNs. Finally, an example is given to demonstrate the effectiveness of the theoretical results.

关键词： Finite-time anti-synchronization memristive neural networks time-varying delays

Network-based synchronous control of memristive neural networks with denial of service attacks

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Network-based synchronous control of memristive neural netwo...

第三十九届中国控制会议

作者： Xinyu Cai Yijun Zhang Zhenpeng Jiang School of Automation Nanjing University of Science and Technology

This letter is concerned with the issue of global asymptotically synchronization of two neural networks with the denial of service attacks in the communication channels. The memristive neural networks which are with memory, adaptability and high parallel processing ability are considered. A master-slave framework with networks attacks are proposed. Compared with the prior literatures, the DoS attack, which can destroy the network communication, has been modeled by Bernoulli distributed variable. Some sufficient conditions are derived to ensure the synchronization of networks by using Lyapunov function ***, a numerical example is given to illustrate the effectiveness of obtained results.

关键词： memristive neural networks Synchronization DoS attacks Network-based