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Neural Processing Letters

, Volume 50, Issue 2, pp 1627–1648 | Cite as

\(\alpha \)-Exponential Stability of Impulsive Fractional-Order Complex-Valued Neural Networks with Time Delays

  • Peng Wan
  • Jigui JianEmail author
Article
  • 139 Downloads

Abstract

This paper investigates the global \(\alpha \)-exponential stability of impulsive fractional-order complex-valued neural networks with time delays. By constructing proper Lyapunov–Krasovskii functional and employing fractional-order complex-valued differential inequality, some sufficient conditions are obtained to ensure the existence, uniqueness and global \(\alpha \)-exponential stability of the equilibrium point for the considered neural networks. Moreover, the exponential convergence rate is estimated, which depends on the parameters and the order of differentiation of system. Finally, one numerical example with simulations is given to illustrate the effectiveness of the obtained results.

Keywords

\(\alpha \)-exponential stability Fractional-order Complex-valued neural network Impulse Delay: inequality technique 

Notes

Acknowledgements

The authors are grateful for the support of the National Natural Science Foundation of China (11601268).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of ScienceChina Three Gorges UniversityYichangChina
  2. 2.Three Gorges Mathematical Research CenterChina Three Gorges UniversityYichangChina

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