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Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with discontinuous activations

Computer Modeling in Engineering & Sciences 2023年第1期134卷 221-239页

作者： Tianyuan Jia Xiangyong Chen Xiurong Yao Feng Zhao Jianlong Qiu School of Automation and Electrical Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of ShandongLinyi UniversityLinyi276005China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and School of AutomationChina University of GeosciencesWuhan430074China

Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this paper.Both continuous and discontinuous activations are considered forMNNs.And the mixed delays which are closer to reality are taken into the system.Besides,two kinds of control schemes are proposed,including feedback and adaptive control strategies.Based on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are acquired.Moreover,the upper bound of settling time(ST)which is independent of the initial values is given.Finally,the feasibility of our theory is attested by simulation examples.

关键词： Memristor-based neural networks fixed-time synchronization mixed delays discontinuous activations adaptive control

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Exponential synchronization of neural networks with discontinuous activations

Exponential synchronization of neural networks with disconti...

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第三十九届中国控制会议

作者： Malika Sader Fuyong Wang Zhongxin Liu Zengqiang Chen College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University

In this paper, we study the exponential synchronization of neural networks with discontinuous activations. Firstly, a useful discontinuous controller is constructed to ensure the exponential synchronization of considered neural networks. Secondly,some sufficient conditions are acquired according to the theory of differential inclusion and Lyapunov functional techniques.Finally, one example is employed to show the flexibility of the results.

关键词： discontinuous activations discontinuous controller Neural networks Exponential synchronization

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Fixed-time stabilization of discontinuous spatiotemporal neural networks with time-varying coefficients via aperiodically switching control

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Science China(Information Sciences) 2023年第5期66卷 182-195页

作者： Xiaofang HU Leimin WANG Chuan-Ke ZHANG Xiongbo WAN Yong HE School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper focuses on the challenge of fixed-time control for spatiotemporal neural networks(SNNs) with discontinuous activations and time-varying coefficients. A novel fixed-time convergence lemma is proposed, which facilitates the handling of time-varying coefficients of SNNs and relaxes the restriction on the non-positive definiteness of the derivative of the Lyapunov function. Besides, a more flexible and economical aperiodically switching control technique is presented to stabilize SNNs within a fixed time,efectively reducing the amount of information transmission and control costs. Under the newly established fixed-time convergence lemma and aperiodically switching controller, many more general algebraic conditions are deduced to ensure the fixed-time stabilization of SNNs. Numerical examples are provided to manifest the validity of the results.

关键词： spatiotemporal neural networks discontinuous activations time-varying coefficients fixed-time stabilization aperiodically switching control

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