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Asymptotical Stability of Riemann‐Liouville Nonlinear Fractional Neutral Neural Networks with Time‐Varying Delays

Author

Listed:
  • Erdal Korkmaz
  • Abdulhamit Ozdemir
  • Kenan Yildirim

Abstract

In this paper, the asymptotic stability of solutions is investigated for a class of nonlinear fractional neutral neural networks with time‐dependent delays which are unbounded. By constructing the appropriate Lyapunov functional, sufficient conditions for asymptotic stability of neural networks are obtained with the help of LMI. An example is presented by using the LMI Toolbox to demonstrate the effectiveness of the obtained results.

Suggested Citation

  • Erdal Korkmaz & Abdulhamit Ozdemir & Kenan Yildirim, 2022. "Asymptotical Stability of Riemann‐Liouville Nonlinear Fractional Neutral Neural Networks with Time‐Varying Delays," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:6832472
    DOI: 10.1155/2022/6832472
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    References listed on IDEAS

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    1. Hai Zhang & Renyu Ye & Song Liu & Jinde Cao & Ahmad Alsaedi & Xiaodi Li, 2018. "LMI-based approach to stability analysis for fractional-order neural networks with discrete and distributed delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(3), pages 537-545, February.
    2. Park, Ju H., 2006. "On global stability criterion for neural networks with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 30(4), pages 897-902.
    3. M. Syed Ali & S. Saravanan & Quanxin Zhu, 2017. "Finite-time stability of neutral-type neural networks with random time-varying delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(15), pages 3279-3295, November.
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