On Variable-Order Fractional Discrete Neural Networks: Solvability and Stability

Abstract

Few papers have been published to date regarding the stability of neural networks described by fractional difference operators. This paper makes a contribution to the topic by presenting a variable-order fractional discrete neural network model and by proving its Ulam–Hyers stability. In particular, two novel theorems are illustrated, one regarding the existence of the solution for the proposed variable-order network and the other regarding its Ulam–Hyers stability. Finally, numerical simulations of three-dimensional and two-dimensional variable-order fractional neural networks were carried out to highlight the effectiveness of the conceived theoretical approach.

Abstract of "On Variable-Order Fractional Discrete Neural Networks: Solvability and Stability" by Amel Hioual, Adel Ouannas, Taki-Eddine Oussaeif et al., https://doi.org/10.3390/fractalfract6020119, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.