Robust filtering for Markovian jumping static neural networks with time-varying delays
The problem of robust H ∞ filtering for Markovian jumping static neural networks with time-varying delays is considered in this paper. The effect of the activation function on the time delays is comprehensively considered. Based on Wirtinger inequality, a new inequality is quoted to solve the Lyapun...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-06-01
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| Series: | Journal of Algorithms & Computational Technology |
| Online Access: | https://doi.org/10.1177/1748302620931340 |
| Summary: | The problem of robust H ∞ filtering for Markovian jumping static neural networks with time-varying delays is considered in this paper. The effect of the activation function on the time delays is comprehensively considered. Based on Wirtinger inequality, a new inequality is quoted to solve the Lyapunov functions with the double-integral terms. Then, a less conservative result on the robust H ∞ filtering is obtained, which guarantees the resulting error systems stochastically stable and satisfies a prescribed H ∞ performance index. The effectiveness of the developed results is finally demonstrated by numerical examples. |
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| ISSN: | 1748-3026 |