Fixed-Time Event-Triggered Impulsive Secure Synchronization of Quaternion-Valued Fuzzy Neural Networks Subject to Stochastic Cyber-Attacks

This article addresses the fixed-time event-triggered impulsive secure synchronization issue of a category of Takagi-Sugeno quaternion-valued fuzzy neural networks (QVFNNs) under stochastic cyber-attacks for the first time. To do this, dynamic event-triggered control, fuzzy rules, and impulsive cont...

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Vydáno v:IEEE transactions on fuzzy systems Ročník 33; číslo 2; s. 559 - 569
Hlavní autoři: Liu, Lirong, Bao, Haibo, Cao, Jinde
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.02.2025
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ISSN:1063-6706, 1941-0034
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Abstract This article addresses the fixed-time event-triggered impulsive secure synchronization issue of a category of Takagi-Sugeno quaternion-valued fuzzy neural networks (QVFNNs) under stochastic cyber-attacks for the first time. To do this, dynamic event-triggered control, fuzzy rules, and impulsive control are combined to create a well-designed event-triggered impulsive control scheme that can significantly decline the consumption cost and communication burden. Meanwhile, in virtue of two different and independent Bernoulli random variables, the stochastic cyber-attack model involving not only denial-of-service attacks but also deception attacks is introduced. Then, some algebraic criteria are deduced to accomplish fixed-time synchronization for the QVFNNs with or without stochastic cyber-attacks through the fuzzy set theory, Lyapunov functional method, and impulsive system theory. Furthermore, the nonexistence of the Zeno phenomenon can be guaranteed. Ultimately, an illustrative instance is revealed to manifest the correctness of the theoretical outcomes and the practicability of the current strategy.
AbstractList This article addresses the fixed-time event-triggered impulsive secure synchronization issue of a category of Takagi-Sugeno quaternion-valued fuzzy neural networks (QVFNNs) under stochastic cyber-attacks for the first time. To do this, dynamic event-triggered control, fuzzy rules, and impulsive control are combined to create a well-designed event-triggered impulsive control scheme that can significantly decline the consumption cost and communication burden. Meanwhile, in virtue of two different and independent Bernoulli random variables, the stochastic cyber-attack model involving not only denial-of-service attacks but also deception attacks is introduced. Then, some algebraic criteria are deduced to accomplish fixed-time synchronization for the QVFNNs with or without stochastic cyber-attacks through the fuzzy set theory, Lyapunov functional method, and impulsive system theory. Furthermore, the nonexistence of the Zeno phenomenon can be guaranteed. Ultimately, an illustrative instance is revealed to manifest the correctness of the theoretical outcomes and the practicability of the current strategy.
Author Bao, Haibo
Liu, Lirong
Cao, Jinde
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Snippet This article addresses the fixed-time event-triggered impulsive secure synchronization issue of a category of Takagi-Sugeno quaternion-valued fuzzy neural...
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SubjectTerms Artificial neural networks
Cyberattack
Delays
Event detection
Event-triggered impulsive control (ETIC)
fixed-time synchronization
Fuzzy neural networks
quaternion-valued fuzzy neural networks (QVFNNs)
Quaternions
Stability criteria
stochastic cyber-attacks
Stochastic processes
Synchronization
Vectors
Title Fixed-Time Event-Triggered Impulsive Secure Synchronization of Quaternion-Valued Fuzzy Neural Networks Subject to Stochastic Cyber-Attacks
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Volume 33
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