首页|H∞/Passive Synchronization of Semi-Markov Jump Neural Networks Subject to Hybrid Attacks via an Activation Function Division Approach

H∞/Passive Synchronization of Semi-Markov Jump Neural Networks Subject to Hybrid Attacks via an Activation Function Division Approach

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In this work,an H∞/passive-based secure synchronization control problem is investigated for continuous-time semi-Markov neural networks subject to hybrid attacks,in which hybrid attacks are the combinations of denial-of-service attacks and deception attacks,and they are described by two groups of independent Bernoulli distributions.On this foundation,via the Lyapunov stability theory and linear matrix inequality technology,the H∞/passive-based performance criteria for semi-Markov jump neural networks are obtained.Additionally,an activation function division approach for neural networks is adopted to further reduce the conservatism of the criteria.Finally,a simulation example is provided to verify the validity and feasibility of the proposed method.

Activation function division approachdeception attacksdenial-of-service attacksH∞/pa-ssive synchronizationsemi-Markov jump neural networks

ZHANG Ziwei、SHEN Hao、SU Lei

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School of Electrical and Information Engineering,Anhui University of Technology,Ma'anshan 243002,China

Anhui Province Key Laboratory of Special Heavy Load Robot and School of Electrical and Information Engi-neering,Anhui University of Technology,Ma'anshan 243002,China

国家自然科学基金国家自然科学基金国家自然科学基金安徽省自然科学基金Natural Science Foundation for Distinguished Young Scholars of Higher Ed-ucation Institutions of Anhui ProvinceNatural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui ProvinceNatural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui ProvinceNatural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui ProvinceMajor Technologies Research and Development Special Program of Anhui Province安徽省重点研发计划

6210300562173001622730062108085QF2762022AH0200342022AH0300492023AH0300302022AH030049202003a05020001202104a05020015

2024

10.1007/s11424-024-3049-8

系统科学与复杂性学报(英文版)
中国科学院系统科学研究所

系统科学与复杂性学报(英文版)

EI
影响因子：0.181
ISSN：1009-6124
年,卷(期)：2024.37(3)
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