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New Methods of Finite-Time Synchronization for a Class of Fractional-Order Delayed Neural Networks

Author

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  • Weiwei Zhang
  • Jinde Cao
  • Ahmed Alsaedi
  • Fuad E. Alsaadi

Abstract

Finite-time synchronization for a class of fractional-order delayed neural networks with fractional order , and , is investigated in this paper. Through the use of Hölder inequality, generalized Bernoulli inequality, and inequality skills, two sufficient conditions are considered to ensure synchronization of fractional-order delayed neural networks in a finite-time interval. Numerical example is given to verify the feasibility of the theoretical results.

Suggested Citation

  • Weiwei Zhang & Jinde Cao & Ahmed Alsaedi & Fuad E. Alsaadi, 2017. "New Methods of Finite-Time Synchronization for a Class of Fractional-Order Delayed Neural Networks," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-9, June.
    • Handle: RePEc:hin:jnlmpe:1804383
    DOI: 10.1155/2017/1804383
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    Cited by:

    1. Du, Feifei & Lu, Jun-Guo, 2021. "New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    2. Babu, N. Ramesh & Balasubramaniam, P., 2022. "Master-slave synchronization of a new fractal-fractional order quaternion-valued neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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