Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/23454
Title: | Nonfragile H<inf>∞</inf>State Estimation for Recurrent Neural Networks with Time-Varying Delays: On Proportional-Integral Observer Design |
Authors: | Zhao, D Wang, Z Wei, G Liu, X |
Keywords: | H∞ performance;nonfragile state estimation;proportional–integral observer (PIO);randomly occurring gain variations (ROGVs);recurrent neural networks (RNNs);time-varying delays (TVDs) |
Issue Date: | 19-Aug-2020 |
Publisher: | IEEE |
Citation: | Zhao, D., Wang, Z., Wei, G. and Liu, X. (2021) 'Nonfragile H<inf>∞</inf>State Estimation for Recurrent Neural Networks with Time-Varying Delays: On Proportional-Integral Observer Design', IEEE Transactions on Neural Networks and Learning Systems, 2021, 32 (8), pp. 3553 - 3565. doi: 10.1109/TNNLS.2020.3015376. |
URI: | https://bura.brunel.ac.uk/handle/2438/23454 |
DOI: | https://doi.org/10.1109/TNNLS.2020.3015376 |
ISSN: | 2162-237X |
Appears in Collections: | Dept of Computer Science Research Papers |
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