Predefined-time synchronization of time-varying delay fractional-order Cohen–Grossberg neural network based on memristor

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Communications in Nonlinear Science and Numerical Simulation Pub Date : 2024-08-28 DOI:10.1016/j.cnsns.2024.108294
Xinyao Cui , Mingwen Zheng , Yanping Zhang , Manman Yuan , Hui Zhao , Yaoming Zhang
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Abstract

This paper delves into the synchronization dynamics of fractional-order memristor Cohen–Grossberg neural network systems with time-varying delays at predefined times (PTS-MFCGNNs). Firstly, leveraging the concept of predefined-time stability, we devise a fractional-order controller, establish sufficient conditions for predefined-time synchronization, and achieve synchronization within the Cohen–Grossberg drive–response system. Secondly, building upon these findings, we scrutinize the synchronization dynamics within the time domain of the PTS-MFCGNNs system. Finally, we validate our theoretical framework through numerical simulations and engage in a comprehensive discussion on predefined-time synchronization within the PTS-MFCGNNs system.

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基于忆阻器的时变延迟分数阶科恩-格罗斯伯格神经网络的预定时间同步化
本文深入研究了具有预定时间时变延迟的分数阶可控硅科恩-格罗斯伯格神经网络系统(PTS-MFCGNN)的同步动力学。首先,利用预定时间稳定性的概念,我们设计了一个分数阶控制器,建立了预定时间同步的充分条件,并在科恩-格罗斯伯格驱动-响应系统内实现了同步。其次,在这些发现的基础上,我们仔细研究了 PTS-MFCGNNs 系统时域内的同步动态。最后,我们通过数值模拟验证了我们的理论框架,并对 PTS-MFCGNNs 系统内的预定义时间同步进行了全面讨论。
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来源期刊
Communications in Nonlinear Science and Numerical Simulation
Communications in Nonlinear Science and Numerical Simulation MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
6.80
自引率
7.70%
发文量
378
审稿时长
78 days
期刊介绍: The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity. The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged. Topics of interest: Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity. No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.
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