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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2023/1335184 |
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| _version_ | 1850168069853282304 |
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| author | Xiaobo Wang Xuefei Wu Zhe Nie Zengxian Yan |
| author_facet | Xiaobo Wang Xuefei Wu Zhe Nie Zengxian Yan |
| author_sort | Xiaobo Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e65602ec1dd94de991f02c7795f0cb80 |
| institution | OA Journals |
| issn | 1099-0526 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e65602ec1dd94de991f02c7795f0cb802025-08-20T02:21:04ZengWileyComplexity1099-05262023-01-01202310.1155/2023/1335184The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic PerturbationsXiaobo Wang0Xuefei Wu1Zhe Nie2Zengxian Yan3College of Economics and ManagementArtificial Intelligence SchoolDigital Creativity and Animation SchoolGuangxi Modern Polytechnic CollegeIn 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.http://dx.doi.org/10.1155/2023/1335184 |
| spellingShingle | Xiaobo Wang Xuefei Wu Zhe Nie Zengxian Yan The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations Complexity |
| title | The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations |
| title_full | The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations |
| title_fullStr | The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations |
| title_full_unstemmed | The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations |
| title_short | The pth Moment Exponential Synchronization of Drive-Response Memristor Neural Networks Subject to Stochastic Perturbations |
| title_sort | pth moment exponential synchronization of drive response memristor neural networks subject to stochastic perturbations |
| url | http://dx.doi.org/10.1155/2023/1335184 |
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