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

  • Yali DongEmail author
  • Huimin Wang
Article
  • 11 Downloads

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.

Keywords

Discrete-time stochastic neural networks Exponentially stabization Output feedback control Lyapunov–Krasovskii functional Time-varying delay 

Notes

Acknowledgements

This work was supported by the Natural Science Foundation of Tianjin under Grant No. 18JCYBJC88000 and the National Nature Science Foundation of China under Grant Nos. 61873186,61603272 and 61703307.

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematical SciencesTianjin Polytechnic UniversityTianjinChina

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