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Neural Processing Letters
Erschienen in: Neural Processing Letters 2/2021

22.03.2021

State Estimation for Markovian Coupled Neural Networks with Multiple Time Delays Via Event-Triggered Mechanism

verfasst von: Yangling Wang, Jinde Cao, Haijun Wang

Erschienen in: Neural Processing Letters | Ausgabe 2/2021

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Abstract

This paper focuses on the state estimation problem for a type of coupled neural networks with multiple time delays and markovian jumping communication topologies. To avoid unnecessary resources consuming, a novel state estimator is designed based on event-triggered mechanism, in which the control input of each node is only updated when the measurement output error exceeds a predefined threshold. The event-triggering time sequence is a subset of the switching time sequence, which can naturally excludes the Zeno-behavior. By utilizing an appropriate Lyapunov-Krasovskii functional, as well as the weak infinitesimal operator of Markov process and some algebraic inequalities, an easy-to-check sufficient criterion is derived to ensure the exponential ultimate boundedness of the estimation error. Finally, a simulation example is presented to illustrate the applications and effectiveness of the theoretical results.
Vorheriger Artikel Quasi-Synchronization of Fractional-Order Complex-Valued Memristive Recurrent Neural Networks with Switching Jumps Mismatch
Nächster Artikel Mutated Cleavages of Images for Stealth Disclosure: A Hopfield Neural Network Attractor (HNNA) Approach

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Metadaten
Titel
State Estimation for Markovian Coupled Neural Networks with Multiple Time Delays Via Event-Triggered Mechanism
verfasst von
Yangling Wang
Jinde Cao
Haijun Wang
Publikationsdatum
22.03.2021
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 2/2021
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-020-10396-4

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