Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: a gain-scheduled approach

DOI10.1016/j.neunet.2020.08.023zbMath1478.93408OpenAlexW3083341821WikidataQ99358267 ScholiaQ99358267MaRDI QIDQ2057759

Shuai Liu, Zidong Wang, Guoliang Wei, Yun Chen

Publication date: 7 December 2021

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2020.08.023

zbMATH Keywords

state estimationartificial neural networksdynamic event triggering mechanismgain-scheduled approachrandomly occurring delaytime-varying probability

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Discrete event control/observation systems (93C65) Delay control/observation systems (93C43) Networked control (93B70)

Related Items (4)

Global Mittag-Leffler stability for fractional-order quaternion-valued neural networks with piecewise constant arguments and impulses ⋮ Set-membership filtering for complex networks with constraint communication channels ⋮ Event‐based joint estimation for unknown inputs and states: A distributed recursive filtering method ⋮ Improved results on \(L_2-L_\infty\) state estimation for neural networks with time-varying delay

Cites Work

• Dynamic event-triggered mechanism for \(H_\infty\) non-fragile state estimation of complex networks under randomly occurring sensor saturations
• An overview of neuronal state estimation of neural networks with time-varying delays
• Delay-distribution-dependent state estimation for neural networks under stochastic communication protocol with uncertain transition probabilities
• Recursive distributed filtering over sensor networks on Gilbert-Elliott channels: a dynamic event-triggered approach
• Finite-time resilient \(H_\infty\) state estimation for discrete-time delayed neural networks under dynamic event-triggered mechanism
• \(H_\infty\) state estimation for multi-rate artificial neural networks with integral measurements: a switched system approach
• Event-Based Recursive Distributed Filtering Over Wireless Sensor Networks
• Dynamic Triggering Mechanisms for Event-Triggered Control
• On stability of cellular neural networks with delay
• Global exponential stability in Lagrange sense for quaternion-valued neural networks with leakage delay and mixed time-varying delays
• Protocol-Based Unscented Kalman Filtering in the Presence of Stochastic Uncertainties
• A Set-Membership Approach to Event-Triggered Filtering for General Nonlinear Systems Over Sensor Networks
• LMI-based approach for asymptotically stability analysis of delayed neural networks

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