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A Global Stability Analysis of Fractional-Order Memristor Fuzzy Bam Neural Networks With Time-Variable Delays and Leakage Term

Author

Listed:
  • K. Meenakshi
  • J. Kumar
  • V. Umesha
  • M. Syed Ali
  • Mohammad Yar
  • S. J. Johnston

Abstract

A global stability analysis of fractional-order memristor fuzzy BAM neural networks with time-varying delays and leakage terms is covered in this paper. Sufficient conditions are established to guarantee uniform stability of fractional-order fuzzy BAM neural networks and to derive the equilibrium point, which ensures asymptotic stability on a global scale, using the theory of fractional-order calculus, the lemma of fractional Barbalat, and the characteristics of fuzzy logic operators. In order to validate the effectiveness of the theoretical conclusions, two numerical examples are provided to illustrate the value of the outcome.

Suggested Citation

  • K. Meenakshi & J. Kumar & V. Umesha & M. Syed Ali & Mohammad Yar & S. J. Johnston, 2026. "A Global Stability Analysis of Fractional-Order Memristor Fuzzy Bam Neural Networks With Time-Variable Delays and Leakage Term," Discrete Dynamics in Nature and Society, Hindawi, vol. 2026, pages 1-16, May.
    • Handle: RePEc:hin:jnddns:1112314
    DOI: 10.1155/ddns/1112314
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