Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks
This paper is concerned with the event-based synchronization control for chaotic neural networks by using a refined discontinuous trigger scheme. To get rid of the Zeno phenomenon and decrease the triggering times, a refined discontinuous event-trigger (RDET) scheme is employed by designing a new th...
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MDPI AG
2025-05-01
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| author | Yingjie Wang Yingjie Fan Meixuan Li |
| author_facet | Yingjie Wang Yingjie Fan Meixuan Li |
| author_sort | Yingjie Wang |
| collection | DOAJ |
| description | This paper is concerned with the event-based synchronization control for chaotic neural networks by using a refined discontinuous trigger scheme. To get rid of the Zeno phenomenon and decrease the triggering times, a refined discontinuous event-trigger (RDET) scheme is employed by designing a new threshold function. The proposed threshold function consists of two parts, i.e., quadratic term and exponential decay term, which makes the derivative of the Lyapunov function possibly not less than zero. On this basis, an important lemma is derived, which contributes to performing a stability analysis. Then, the corresponding closed-loop system model is established in the presence of a trigger scheme. Then, a time-dependent Lyapunov function (TLF) method is established based on the features of an RDET. In view of inequality estimation techniques and stability theory, some synchronization criteria are developed to guarantee that the synchronization of chaotic neural networks can be realized by using the novel discontinuous event-trigger schemes. Finally, a Hopfield neural network is displayed to demonstrate the advantages and effectiveness of the derived results. |
| format | Article |
| id | doaj-art-e1c28b34c5f44094b9b2d8abd2d78ef5 |
| institution | OA Journals |
| issn | 2075-1680 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Axioms |
| spelling | doaj-art-e1c28b34c5f44094b9b2d8abd2d78ef52025-08-20T02:24:26ZengMDPI AGAxioms2075-16802025-05-0114640310.3390/axioms14060403Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural NetworksYingjie Wang0Yingjie Fan1Meixuan Li2College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, ChinaSchool of Science, Qingdao University of Technology, Qingdao 266520, ChinaThis paper is concerned with the event-based synchronization control for chaotic neural networks by using a refined discontinuous trigger scheme. To get rid of the Zeno phenomenon and decrease the triggering times, a refined discontinuous event-trigger (RDET) scheme is employed by designing a new threshold function. The proposed threshold function consists of two parts, i.e., quadratic term and exponential decay term, which makes the derivative of the Lyapunov function possibly not less than zero. On this basis, an important lemma is derived, which contributes to performing a stability analysis. Then, the corresponding closed-loop system model is established in the presence of a trigger scheme. Then, a time-dependent Lyapunov function (TLF) method is established based on the features of an RDET. In view of inequality estimation techniques and stability theory, some synchronization criteria are developed to guarantee that the synchronization of chaotic neural networks can be realized by using the novel discontinuous event-trigger schemes. Finally, a Hopfield neural network is displayed to demonstrate the advantages and effectiveness of the derived results.https://www.mdpi.com/2075-1680/14/6/403refined discontinuous event-trigger schemesynchronizationchaotic neural networkstime-dependent Lyapunov function |
| spellingShingle | Yingjie Wang Yingjie Fan Meixuan Li Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks Axioms refined discontinuous event-trigger scheme synchronization chaotic neural networks time-dependent Lyapunov function |
| title | Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks |
| title_full | Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks |
| title_fullStr | Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks |
| title_full_unstemmed | Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks |
| title_short | Refined Discontinuous Trigger Scheme for Event-Based Synchronization of Chaotic Neural Networks |
| title_sort | refined discontinuous trigger scheme for event based synchronization of chaotic neural networks |
| topic | refined discontinuous event-trigger scheme synchronization chaotic neural networks time-dependent Lyapunov function |
| url | https://www.mdpi.com/2075-1680/14/6/403 |
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