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
Main Authors: Xiaobo Wang, Xuefei Wu, Zhe Nie, Zengxian Yan
Format: Article
Language:English
Published: Hindawi-Wiley 2023-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2023/1335184
Description
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.
ISSN:1099-0526