ρ$$ \rho $$-Caputo 神经网络系统的有限时间稳定性

IF 2.7 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Asian Journal of Control Pub Date : 2024-06-20 DOI:10.1002/asjc.3447

Mohamed Rhaima, Liping Chen, Lassaad Mchiri, Abdellatif Ben Makhlouf

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引用次数: 0

摘要

在本文中，我们将研究阶数为.的-卡普托神经网络分数系统（NNFS）的有限时间稳定性（FTS）。利用技术不等式（如格伦沃尔不等式和赫尔德不等式），我们提出了一些有限时间稳定性结果。我们提供了两个数值示例来说明理论发现。

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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Finite time stability of ρ$$ \rho $$‐Caputo neural network systems

In this article, we will examine the finite time stability (FTS) of ‐Caputo neural network fractional systems (NNFS) with an order of . Utilizing technical inequalities such as Gronwall and Hölder inequalities, we present some FTS results. Two numerical examples are provided to illustrate the theoretical findings.

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来源期刊

Asian Journal of Control 工程技术-自动化与控制系统

CiteScore

4.80

自引率

25.00%

发文量

253

审稿时长

7.2 months

期刊介绍： The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.

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