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Finite-Time Stability for Caputo–Katugampola Fractional-Order Time-Delayed Neural Networks

  • Assaad Jmal
  • Abdellatif Ben Makhlouf
  • A. M. NagyEmail author
  • Omar Naifar
Article

Abstract

In this paper, an original scheme is presented, in order to study the finite-time stability of the equilibrium point, and to prove its existence and uniqueness, for Caputo–Katugampola fractional-order neural networks, with time delay. The proposed scheme uses a newly introduced fractional derivative concept in the literature, which is the Caputo–Katugampola fractional derivative. The effectiveness of the theoretical results is shown through simulations for two numerical examples.

Keywords

Fractional-order calculus Neural networks Finite-time stability Caputo–Katugampola derivative 

Notes

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflicts of interest.

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

Authors and Affiliations

  1. 1.Control and Energy Management Laboratory, National School of EngineeringSfax UniversitySfaxTunisia
  2. 2.Department of Mathematics, College of ScienceJouf UniversityAljoufSaudi Arabia
  3. 3.Department of Mathematics, Faculty of ScienceKuwait UniversitySafatKuwait
  4. 4.Department of Mathematics, Faculty of ScienceBenha UniversityBenhaEgypt

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