Nonfragile State Estimator Design for Memristor-Based Fractional-Order Neural Networks with Randomly Occurring Hybrid Time Delays and Stochastic Cyber-Attacks

Nonfragile State Estimator Design for Memristor-Based Fractional-Order Neural Networks with Randomly Occurring Hybrid Time Delays and Stochastic Cyber-Attacks

This paper addresses the design of nonfragile state estimators for memristor-based fractional-order neural networks that are subject to stochastic cyber-attacks and hybrid time delays. To mitigate the issue of limited bandwidth during signal transmission, quantitative processing is introduced to red...

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Bibliographic Details
Main Authors: Qifeng Niu, Xiaoguang Shao, Yanjuan Lu, Yibo Zhao, Jie Zhang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Fractal and Fractional
Subjects:
memristor-based neural networks
nonfragile estimation
fractional-order
cyber-attacks
Online Access:https://www.mdpi.com/2504-3110/9/7/447
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