Variance-constrained resilient H∞ $H_{\infty }$ state estimation for time-varying neural networks with randomly varying nonlinearities and missing measurements
Abstract This paper addresses the resilient H∞ $H_{\infty }$ state estimation problem under variance constraint for discrete uncertain time-varying recurrent neural networks with randomly varying nonlinearities and missing measurements. The phenomena of missing measurements and randomly varying nonl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2019-09-01
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| Series: | Advances in Difference Equations |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13662-019-2298-7 |