{"title":"Fast finite-time quantized control of multi-layer networks and its applications in secure communication","authors":"Qian Tang , Shaocheng Qu , Wei Zheng , Zhengwen Tu","doi":"10.1016/j.neunet.2025.107225","DOIUrl":null,"url":null,"abstract":"<div><div>This paper introduces a quantized controller to address the challenge of fast finite-time synchronization of multi-layer networks, where each layer represents a distinct type of interaction within complex systems. Firstly, based on the stability theory, a novel fast finite-time stability criterion is derived, which can set a smaller upper limit of the settling time by comparing it with the general finite-time stability. Secondly, by converting continuous error signals into piecewise continuous forms, a quantized control scheme is employed to realize fast finite-time synchronization in multi-layer networks, which can save control resources and alleviate communication congestion. Finally, the feasibility of the quantized control algorithm in multi-layer network synchronization and its applications in secure communication are verified through numerical simulation.</div></div>","PeriodicalId":49763,"journal":{"name":"Neural Networks","volume":"185 ","pages":"Article 107225"},"PeriodicalIF":6.0000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0893608025001042","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a quantized controller to address the challenge of fast finite-time synchronization of multi-layer networks, where each layer represents a distinct type of interaction within complex systems. Firstly, based on the stability theory, a novel fast finite-time stability criterion is derived, which can set a smaller upper limit of the settling time by comparing it with the general finite-time stability. Secondly, by converting continuous error signals into piecewise continuous forms, a quantized control scheme is employed to realize fast finite-time synchronization in multi-layer networks, which can save control resources and alleviate communication congestion. Finally, the feasibility of the quantized control algorithm in multi-layer network synchronization and its applications in secure communication are verified through numerical simulation.
期刊介绍:
Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.