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Resilient fixed-time synchronization of delayed fuzzy memristive reaction-diffusion neural networks under DoS attacks

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成果类型:
期刊论文
作者:
Xiao, Qizhen;Liu, Hongliang;Luo, Zhiyong
通讯作者:
Liu, HL
作者机构:
[Xiao, Qizhen; Liu, Hongliang; Liu, HL; Luo, Zhiyong] Univ South China, Sch Math & Phys, Hengyang 421001, Peoples R China.
[Xiao, Qizhen; Liu, Hongliang; Liu, HL] Univ South China, Hunan Key Lab Math Modeling & Sci Comp, Hengyang 421001, Peoples R China.
通讯机构:
[Liu, HL ] U
Univ South China, Sch Math & Phys, Hengyang 421001, Peoples R China.
Univ South China, Hunan Key Lab Math Modeling & Sci Comp, Hengyang 421001, Peoples R China.
语种:
英文
关键词:
Aperiodic DoS attacks;Resilient synchronization;Fixed-time stability;Fuzzy neural networks;Reaction-diffusion terms
期刊:
Fuzzy Sets and Systems
ISSN:
0165-0114
年:
2024
卷:
479
页码:
108856
基金类别:
Scientific Research Foundation of Hunan Provincial Education Department#&#&#20A425 Natural Science Foundation of Hunan Province
机构署名:
本校为第一且通讯机构
院系归属:
数理学院
摘要:
This work focuses on the resilient fixed -time synchronization of delayed fuzzy memristive reaction -diffusion neural networks under denial -of -service (DoS) attacks. To efficaciously tolerate the aperiodic DoS attacks, a new appropriate controller is designed to ensure the fixed -time resilient synchronization of the systems. Moreover, two mild sufficient conditions are first proposed and the constrained techniques of attacking intervals are employed to overcome the challenge of estimating the upper bound of the settling time under aperiodic DoS attacks. Lastly, an example is utilized to ill...

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