Finite-Time Synchronization of Coupled Memristive Neural Networks Subject to Stochastic Link Uncertainties and Attacks

This paper deals with the finite-time synchronization problem of coupled memristive neural networks with time-delays. The coupling among the nodes is perturbed by a multiplicative stochastic uncertainty. The coupled networks under consideration are subject to Denial-of-Service (DoS) attacks and each...

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Published inChinese Control Conference pp. 5333 - 5338
Main Authors Lu, Qingqing, Zhang, Xiaomei, Sheng, Suying
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 01.07.2019
Subjects
Coupled Neural Networks
Couplings
Denial-of-service attack
DoS Attacks
Finite-Time Synchronization
Memristor
Neural networks
Stochastic processes
Symmetric matrices
Synchronization
Uncertainty
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Abstract This paper deals with the finite-time synchronization problem of coupled memristive neural networks with time-delays. The coupling among the nodes is perturbed by a multiplicative stochastic uncertainty. The coupled networks under consideration are subject to Denial-of-Service (DoS) attacks and each node has an interval time-varying delay. DoS attacks occur in a random fashion which is governed by a Bernoulli stochastic variable. By applying the Lyapunov functional method and some mathematical techniques, the finite-time synchronization conditions are established. One numerical example is given to show the effectiveness of the proposed algorithm.
AbstractList This paper deals with the finite-time synchronization problem of coupled memristive neural networks with time-delays. The coupling among the nodes is perturbed by a multiplicative stochastic uncertainty. The coupled networks under consideration are subject to Denial-of-Service (DoS) attacks and each node has an interval time-varying delay. DoS attacks occur in a random fashion which is governed by a Bernoulli stochastic variable. By applying the Lyapunov functional method and some mathematical techniques, the finite-time synchronization conditions are established. One numerical example is given to show the effectiveness of the proposed algorithm.
Author Lu, Qingqing
Sheng, Suying
Zhang, Xiaomei
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  organization: School of Information Science and Technology, Nantong University, Nantong, Jiangsu, 226019, >P. R. China
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Snippet This paper deals with the finite-time synchronization problem of coupled memristive neural networks with time-delays. The coupling among the nodes is perturbed...
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SubjectTerms Coupled Neural Networks
Couplings
Denial-of-service attack
DoS Attacks
Finite-Time Synchronization
Memristor
Neural networks
Stochastic processes
Symmetric matrices
Synchronization
Uncertainty
Title Finite-Time Synchronization of Coupled Memristive Neural Networks Subject to Stochastic Link Uncertainties and Attacks
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