Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy
This paper proposes the event-triggered strategy (ETS) for multiple neural networks (NNs) with parameter uncertainty and time delay. By establishing event-triggered mechanism and using matrix inequality techniques, several sufficient criteria are obtained to ensure global robust exponential synchron...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/7672068 |
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| _version_ | 1832550943360548864 |
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| author | Jin-E Zhang Huan Liu |
| author_facet | Jin-E Zhang Huan Liu |
| author_sort | Jin-E Zhang |
| collection | DOAJ |
| description | This paper proposes the event-triggered strategy (ETS) for multiple neural networks (NNs) with parameter uncertainty and time delay. By establishing event-triggered mechanism and using matrix inequality techniques, several sufficient criteria are obtained to ensure global robust exponential synchronization of coupling NNs. In particular, the coupling matrix need not be the Laplace matrix in this paper. In addition, the lower bounds of sampling time intervals are also found by the established event-triggered mechanism. Eventually, three numerical examples are offered to illustrate the obtained results. |
| format | Article |
| id | doaj-art-e430faf8a97b4881b69fdd9f03e45763 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e430faf8a97b4881b69fdd9f03e457632025-02-03T06:05:23ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/76720687672068Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered StrategyJin-E Zhang0Huan Liu1Hubei Normal University, Hubei 435002, ChinaHubei Normal University, Hubei 435002, ChinaThis paper proposes the event-triggered strategy (ETS) for multiple neural networks (NNs) with parameter uncertainty and time delay. By establishing event-triggered mechanism and using matrix inequality techniques, several sufficient criteria are obtained to ensure global robust exponential synchronization of coupling NNs. In particular, the coupling matrix need not be the Laplace matrix in this paper. In addition, the lower bounds of sampling time intervals are also found by the established event-triggered mechanism. Eventually, three numerical examples are offered to illustrate the obtained results.http://dx.doi.org/10.1155/2019/7672068 |
| spellingShingle | Jin-E Zhang Huan Liu Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy Complexity |
| title | Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy |
| title_full | Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy |
| title_fullStr | Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy |
| title_full_unstemmed | Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy |
| title_short | Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy |
| title_sort | global robust exponential synchronization of multiple uncertain neural networks subject to event triggered strategy |
| url | http://dx.doi.org/10.1155/2019/7672068 |
| work_keys_str_mv | AT jinezhang globalrobustexponentialsynchronizationofmultipleuncertainneuralnetworkssubjecttoeventtriggeredstrategy AT huanliu globalrobustexponentialsynchronizationofmultipleuncertainneuralnetworkssubjecttoeventtriggeredstrategy |