A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks
This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov functional, called complete sampling-interval-dependent discontinuous Lyapunov functional, which can adequately capture sampling information on both intervals from...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/72102 |
| _version_ | 1848762660315725824 |
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| author | Xiao, S. Lian, H. Teo, Kok Lay Zeng, H. Zhang, X. |
| author_facet | Xiao, S. Lian, H. Teo, Kok Lay Zeng, H. Zhang, X. |
| author_sort | Xiao, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov functional, called complete sampling-interval-dependent discontinuous Lyapunov functional, which can adequately capture sampling information on both intervals from r(t-t¯) to r(tk-t¯) and from r(t-t¯) to r(tk+1-t¯). Based on this Lyapunov functional and an improved integral inequality, less conservative conditions are derived to ensure the stability of the synchronization error system, leading to the fact that the drive neural network is synchronized with the response neural network. The desired sampled-data controller is designed in terms of solutions to linear matrix inequalities. A numerical example is provided to demonstrate that the proposed approaches are effective and superior to some existing ones in the literature. |
| first_indexed | 2025-11-14T10:51:06Z |
| format | Journal Article |
| id | curtin-20.500.11937-72102 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:51:06Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-721022019-03-22T01:44:02Z A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks Xiao, S. Lian, H. Teo, Kok Lay Zeng, H. Zhang, X. This paper discusses the problem of synchronization for delayed neural networks using sampled-data control. We introduce a new Lyapunov functional, called complete sampling-interval-dependent discontinuous Lyapunov functional, which can adequately capture sampling information on both intervals from r(t-t¯) to r(tk-t¯) and from r(t-t¯) to r(tk+1-t¯). Based on this Lyapunov functional and an improved integral inequality, less conservative conditions are derived to ensure the stability of the synchronization error system, leading to the fact that the drive neural network is synchronized with the response neural network. The desired sampled-data controller is designed in terms of solutions to linear matrix inequalities. A numerical example is provided to demonstrate that the proposed approaches are effective and superior to some existing ones in the literature. 2018 Journal Article http://hdl.handle.net/20.500.11937/72102 10.1016/j.jfranklin.2018.09.022 Elsevier restricted |
| spellingShingle | Xiao, S. Lian, H. Teo, Kok Lay Zeng, H. Zhang, X. A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title | A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title_full | A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title_fullStr | A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title_full_unstemmed | A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title_short | A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| title_sort | new lyapunov functional approach to sampled-data synchronization control for delayed neural networks |
| url | http://hdl.handle.net/20.500.11937/72102 |