AIMS Mathematics (Jan 2021)

Stability analysis of stochastic fractional-order competitive neural networks with leakage delay

  • M. Syed Ali,
  • M. Hymavathi,
  • Bandana Priya,
  • Syeda Asma Kauser,
  • Ganesh Kumar Thakur

DOI
https://doi.org/10.3934/math.2021193
Journal volume & issue
Vol. 6, no. 4
pp. 3205 – 3241

Abstract

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This article, we explore the stability analysis of stochastic fractional-order competitive neural networks with leakage delay. The main objective of this paper is to establish a new set of sufficient conditions, which is for the uniform stability in mean square of such stochastic fractional-order neural networks with leakage. Specifically, the presence and uniqueness of arrangements and stability in mean square for a class of stochastic fractional-order neural systems with delays are concentrated by using Cauchy-Schwartz inequality, Burkholder-Davis-Gundy inequality, Banach fixed point principle and stochastic analysis theory, respectively. Finally, four numerical recreations are given to confirm the hypothetical discoveries.

Keywords