Outlier-resistant l2-l∞ state estimation for discrete-time memristive neural networks with time-delays
In this paper, the outlier-resistant $ l_2 $ - $ l_\infty $ state estimation issue is investigated for a class of discrete-time memristive neural networks (DMNNs) with time-delays. Measurement outputs could occur unpredictable abnormal data due possibly to outliers from abnormal interferences, cyber...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-01-01
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| Series: | Systems Science & Control Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21642583.2020.1867663 |