The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations

In this paper, the pth moment exponential synchronization problems of drive-response stochastic memristor neural networks are studied via a state feedback controller. The dynamics of the memristor neural network are nonidentical, consisting of both asymmetrically nondelayed and delayed coupled, stat...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2023; pp. 1 - 10
Main Authors Wang, Xiaobo, Wu, Xuefei, Nie, Zhe, Yan, Zengxian
Format Journal Article
LanguageEnglish
Published Hoboken Hindawi 18.07.2023
John Wiley & Sons, Inc
Wiley
Subjects
Brain research
Euclidean space
Feedback control
Memristors
Neural networks
Perturbation
Random variables
Regularization
Signal processing
State feedback
Synchronism
Iran
China
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Summary:In this paper, the pth moment exponential synchronization problems of drive-response stochastic memristor neural networks are studied via a state feedback controller. The dynamics of the memristor neural network are nonidentical, consisting of both asymmetrically nondelayed and delayed coupled, state-dependent, and subject to exogenous stochastic perturbations. The pth moment exponential synchronization of these drive-response stochastic memristor neural networks is guaranteed under some testable and computable sufficient conditions utilizing differential inclusion theory and Filippov regularization. Finally, the correctness and effectiveness of our theoretical results are demonstrated through a numerical example.
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ISSN:1076-2787
1099-0526
DOI:10.1155/2023/1335184