Stability and Solvability of Discrete Generalized Proportional Caputo Fractional Neural Network Models
Abstract
This study examines the stability in variable-order fractional discrete neural networks modeled via the generalized proportional Caputo fractional difference operator. By employing the Krasnoselskii fixed-point theorem, we establish solution existence under Lipschitz continuity, and we prove Ulam–Hyers stability. Numerical simulations validate that balancing network parameters and fractional orders ensure robustness.
Fields of Study & Subjects
Neural Networks Stability and Synchronization
Fractional Differential Equations Solutions
Mathematical and Theoretical Epidemiology and Ecology Models
Publication details
- Journal / source
- SARAJEVO JOURNAL OF MATHEMATICS
- Publisher
- Academy of Sciences and Arts of Bosnia and Herzegovina
- Volume
- 21
- Issue
- 02
- Publication date
- 4 February 2026