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

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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.

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Authors and Affiliations

  1. Control and Energy Management Laboratory, National School of Engineering, Sfax University, BP 1173, 3038, Sfax, Tunisia

    Assaad Jmal & Omar Naifar

  2. Department of Mathematics, College of Science, Jouf University, Aljouf, Saudi Arabia

    Abdellatif Ben Makhlouf

  3. Department of Mathematics, Faculty of Science, Kuwait University, 13060, Safat, Kuwait

    A. M. Nagy

  4. Department of Mathematics, Faculty of Science, Benha University, Benha, 13518, Egypt

    A. M. Nagy

Authors
  1. Assaad Jmal
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  2. Abdellatif Ben Makhlouf
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  3. A. M. Nagy
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  4. Omar Naifar
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Correspondence to A. M. Nagy.

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Jmal, A., Ben Makhlouf, A., Nagy, A.M. et al. Finite-Time Stability for Caputo–Katugampola Fractional-Order Time-Delayed Neural Networks. Neural Process Lett 50, 607–621 (2019). https://doi.org/10.1007/s11063-019-10060-6

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