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 |