递归反馈反演控制神经元爆破同步

IF 1.2 4区计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS

Archives of Control Sciences Pub Date : 2023-07-20 DOI:10.24425/ACS.2019.131229

S. Rasappan

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引用次数: 2

摘要

J.L. Hindmarsh和R.M. Rose提出了神经元爆发的概念。本文研究了用递归反馈反步控制构造神经元爆发模型的同步问题。利用李雅普诺夫稳定性理论，建立了神经元爆炸系统的同步模型。回溯方案是一个递归过程，将李雅普诺夫函数的选择与控制器的设计联系起来。反步控制方法对同一系统的同步是有效且方便的。通过数值仿真验证了本文的同步结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Synchronization of neuronal bursting using backstepping control with recursive feedback

J.L. Hindmarsh, R.M. Rose introduced the concept of neuronal burst. In this paper, synchronization is investigated for the construction of a model of neuronal burst using backstepping control with recursive feedback. Synchronization for a model of neuronal bursting system is established using Lyapunov stability theory. The backstepping scheme is a recursive procedure that links the choice of a Lyapunov function with the design of a controller. The backstepping control method is effective and convenient to synchronize identical systems. Numerical simulations are furnished to illustrate and validate the synchronization result derived in this paper.

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来源期刊

Archives of Control Sciences Mathematics-Modeling and Simulation

CiteScore

2.40

自引率

33.30%

发文量

审稿时长

14 weeks

期刊介绍： Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.