Event-Triggered H∞ Filtering for Markovian Jump Neural Networks under Random Missing Measurements and Deception Attacks
This paper concentrates on the event-triggered H∞ filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a shared communication network which is vul...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4151542 |
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