Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate
In this paper, a class of discrete-time delayed switched neural networks with dynamic event-triggered mechanism (DETM) and constrained bit rate is considered. In order to reduce the transmission frequency and alleviate the unnecessary resource loss between sensor and estimator, a DETM is proposed. T...
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| Format: | Article |
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Taylor & Francis Group
2024-12-01
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| Series: | Systems Science & Control Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21642583.2024.2334304 |
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| author | Ran Zhang Hongjian Liu Yufei Liu Hailong Tan |
| author_facet | Ran Zhang Hongjian Liu Yufei Liu Hailong Tan |
| author_sort | Ran Zhang |
| collection | DOAJ |
| description | In this paper, a class of discrete-time delayed switched neural networks with dynamic event-triggered mechanism (DETM) and constrained bit rate is considered. In order to reduce the transmission frequency and alleviate the unnecessary resource loss between sensor and estimator, a DETM is proposed. The data transmission from sensor to estimator is realized through constrained bit rate channel. Therefore, in order to reflect the bandwidth allocation rules of accessible neurone nodes, a bit rate constraint model is introduced and an encoding-decoding mechanism is developed. This paper is concerned with the strategy of average dwell time (ADT) and linear matrix inequality, then sufficient conditions for the exponential ultimate boundedness of switched neural networks with DETM and constrained bit rate are proposed. Finally, an example is given to prove the effectiveness of the results. |
| format | Article |
| id | doaj-art-417fa5d5be1f4400a7ed749536f5af5e |
| institution | Kabale University |
| issn | 2164-2583 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Systems Science & Control Engineering |
| spelling | doaj-art-417fa5d5be1f4400a7ed749536f5af5e2024-12-17T09:06:12ZengTaylor & Francis GroupSystems Science & Control Engineering2164-25832024-12-0112110.1080/21642583.2024.2334304Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rateRan Zhang0Hongjian Liu1Yufei Liu2Hailong Tan3School of Electrical Engineering, Anhui Polytechnic University, Wuhu, People's Republic of ChinaKey Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu, People's Republic of ChinaSchool of Electrical Engineering, Anhui Polytechnic University, Wuhu, People's Republic of ChinaKey Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu, People's Republic of ChinaIn this paper, a class of discrete-time delayed switched neural networks with dynamic event-triggered mechanism (DETM) and constrained bit rate is considered. In order to reduce the transmission frequency and alleviate the unnecessary resource loss between sensor and estimator, a DETM is proposed. The data transmission from sensor to estimator is realized through constrained bit rate channel. Therefore, in order to reflect the bandwidth allocation rules of accessible neurone nodes, a bit rate constraint model is introduced and an encoding-decoding mechanism is developed. This paper is concerned with the strategy of average dwell time (ADT) and linear matrix inequality, then sufficient conditions for the exponential ultimate boundedness of switched neural networks with DETM and constrained bit rate are proposed. Finally, an example is given to prove the effectiveness of the results.https://www.tandfonline.com/doi/10.1080/21642583.2024.2334304Switched neural networksdynamic event-triggered mechanismconstrained bit rateaverage dwell time |
| spellingShingle | Ran Zhang Hongjian Liu Yufei Liu Hailong Tan Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate Systems Science & Control Engineering Switched neural networks dynamic event-triggered mechanism constrained bit rate average dwell time |
| title | Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate |
| title_full | Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate |
| title_fullStr | Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate |
| title_full_unstemmed | Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate |
| title_short | Dynamic event-triggered state estimation for discrete-time delayed switched neural networks with constrained bit rate |
| title_sort | dynamic event triggered state estimation for discrete time delayed switched neural networks with constrained bit rate |
| topic | Switched neural networks dynamic event-triggered mechanism constrained bit rate average dwell time |
| url | https://www.tandfonline.com/doi/10.1080/21642583.2024.2334304 |
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