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Neural Processing Letters

Dynamic Event-Triggered Passive Synchronization for Mode-Dependent Persistent Dwell-Time Switched Neural Networks Subject to DoS Attacks

  • 17-10-2023
Published in:
Authors
Xiaomin Wang
Jianwei Xia
Lei Su
Hao Shen
Published in
Neural Processing Letters | Issue 9/2023

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Abstract

The article delves into the critical issue of synchronization in neural networks, focusing on mode-dependent persistent dwell-time switching rules and the impact of Denial of Service (DoS) attacks. It introduces a dynamic event-triggering mechanism to improve network transmission efficiency and presents a novel approach to ensure system stability and security under malicious network attacks. The use of activation function dividing method further reduces conservatism, making the results more practical and applicable. The paper concludes with a numerical example and an image encryption algorithm to demonstrate the effectiveness of the proposed methods, highlighting the significance of this work in advancing the field of neural network synchronization and control.
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previous article CTLC: A Co-Training-Based Label Correction Method for Webly-Supervised Learning
next article Multisynchronization of Delayed Fractional-Order Neural Networks via Average Impulsive Interval
Title
Dynamic Event-Triggered Passive Synchronization for Mode-Dependent Persistent Dwell-Time Switched Neural Networks Subject to DoS Attacks
Authors
Xiaomin Wang
Jianwei Xia
Lei Su
Hao Shen
Publication date
17-10-2023
Publisher
Springer US
Published in
Neural Processing Letters / Issue 9/2023
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-023-11426-7
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