Global Exponential Synchronization of the Memristor-Based Fuzzy Cellular Neural Networks via the Delayed Impulsive Control
The paper studies the global exponential synchronization problem of the memristor-based fuzzy cellular neural networks. First, by utilizing the Filippov solution and the measurable selection theorems, the memristor-based fuzzy cellular neural network is transformed into a kind of neural network with...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Editorial Department of Journal of Nantong University (Natural Science Edition)
2020-03-01
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| Series: | Nantong Daxue xuebao. Ziran kexue ban |
| Subjects: | |
| Online Access: | https://ngzk.cbpt.cnki.net/portal/journal/portal/client/paper/NGZK_c9efeac2-9c05-4fdd-95ce-24e038a7ac16 |
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| Summary: | The paper studies the global exponential synchronization problem of the memristor-based fuzzy cellular neural networks. First, by utilizing the Filippov solution and the measurable selection theorems, the memristor-based fuzzy cellular neural network is transformed into a kind of neural network with the uncertain parameters. In addition,the novel fuzzy inequalities are given to solve the parameter uncertainty problem of the fuzzy feedback connection weight. Then, by designing a delayed impulsive controller and utilizing the concept of the Filippov solution, the delayed impulsive inequalities and the novel fuzzy inequalities, the results of the exponential synchronization between the driving memristor-based fuzzy cellular neural networks and the response memristor-based fuzzy cellular neural networks are obtained. Finally, a numerical example is given to illustrate the effectiveness of theoretical results. The results show that the drive-response system of the memristor-based fuzzy cellular neural networks can be exponentially synchronized by designing a proper controller. |
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| ISSN: | 1673-2340 |