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Neural Processing Letters
Erschienen in: Neural Processing Letters 1/2020

12.07.2019

Robust Output Feedback Stabilization for Uncertain Discrete-Time Stochastic Neural Networks with Time-Varying Delay

verfasst von: Yali Dong, Huimin Wang

Erschienen in: Neural Processing Letters | Ausgabe 1/2020

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Abstract

This paper investigates the problem of robust exponential stabilization of uncertain discrete-time stochastic neural networks with time-varying delay based on output feedback control. By choosing an augmented Lyapunov–Krasovskii functional, we established the sufficient conditions of the delay-dependent asymptotical stabilization in the mean square for a class of discrete-time stochastic neural networks with time-varying delay. Furthermore, we obtain the criteria of robust global exponential stabilization in the mean square for uncertain discrete-time stochastic neural networks with time-varying delay. Finally, we give numerical examples to illustrate the effectiveness of the proposed results.
Vorheriger Artikel Finite-Time Stabilization for Static Neural Networks with Leakage Delay and Time-Varying Delay
Nächster Artikel Methodologies of Compressing a Stable Performance Convolutional Neural Networks in Image Classification

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Metadaten
Titel
Robust Output Feedback Stabilization for Uncertain Discrete-Time Stochastic Neural Networks with Time-Varying Delay
verfasst von
Yali Dong
Huimin Wang
Publikationsdatum
12.07.2019
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 1/2020
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-019-10077-x

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