Dynamic event-triggered state estimation for Markov jump neural networks with partially unknown probabilities
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Tao, Jie 
ORCID: 0000-0001-5037-9010, Xiao, Zehui ORCID: 0000-0002-6847-7249, Li, Zeyu, Wu, Jun ORCID: 0000-0002-1388-7451, Lu, Renquan ORCID: 0000-0003-1084-8243, Shi, Peng ORCID: 0000-0001-8218-586X and Wang, Xiaofeng ORCID: 0000-0003-0144-5944
(2021)
Dynamic event-triggered state estimation for Markov jump neural networks with partially unknown probabilities.
IEEE Transactions on Neural Networks and Learning Systems, 33 (12).
pp. 7438-7447.
ISSN 2162-237X
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/46219 |
| DOI | 10.1109/TNNLS.2021.3085001 |
| Official URL | https://ieeexplore.ieee.org/document/9451548 |
| Subjects | Current > FOR (2020) Classification > 4602 Artificial intelligence Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | Markov, neural networks, Lyapunov techniques, asynchronisation constraint |
| Download/View statistics | View download statistics for this item |
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