具有时间延迟和不确定性的离散时间分数阶 T-S 模糊复值神经网络的完全同步化

IF 10.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Rong Chen;Hong-Li Li;Heng Liu;Haijun Jiang;Jinde Cao
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引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complete Synchronization of Discrete-Time Fractional-Order T-S Fuzzy Complex-Valued Neural Networks With Time Delays and Uncertainties
This article aims to probe synchronization problem of discrete-time fractional-order T-S fuzzy complex-valued neural networks (DFTSFCNNs) with time delays and uncertainties. First, three important power-law inequalities regarding Caputo fractional $\theta$-difference are strictly attested. Next, a fuzzy $m$-norm Lyapunov function (FMLF) that relies on membership functions is designed to replace traditional Lyapunov functions and obtain synchronization criteria. Then, a unique complex-valued fuzzy nonlinear delayed feedback controller is devised, and by virtue of the FMLF method and newly derived inequalities herein, several sufficient criteria are derived to ensure complete synchronization of DFTSFCNNs. Lastly, the validity of the main results is demonstrated by numerical simulations, and an application of the obtained results in image encryption is also provided.
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来源期刊
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems 工程技术-工程:电子与电气
CiteScore
20.50
自引率
13.40%
发文量
517
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Fuzzy Systems is a scholarly journal that focuses on the theory, design, and application of fuzzy systems. It aims to publish high-quality technical papers that contribute significant technical knowledge and exploratory developments in the field of fuzzy systems. The journal particularly emphasizes engineering systems and scientific applications. In addition to research articles, the Transactions also includes a letters section featuring current information, comments, and rebuttals related to published papers.
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