| publication name | Finite-Time Stability for Caputo–Katugampola Fractional-Order Time-Delayed Neural Networks |
|---|---|
| Authors | Assaad Jmal, Abdellatif Ben Makhlouf, A. M. Nagy, Omar Naifar |
| year | 2019 |
| keywords | |
| journal | Neural Processing Letters |
| volume | 50 |
| issue | 1 |
| pages | 607-621 |
| publisher | Not Available |
| Local/International | International |
| Paper Link | https://doi.org/10.1007/s11063-019-10060-6 |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
In this paper, an original scheme is presented, in order to study the finite-time stability of the equilibrium point, and to prove its existence and uniqueness, for Caputo–Katugampola fractional-order neural networks, with time delay. The proposed scheme uses a newly introduced fractional derivative concept in the literature, which is the Caputo–Katugampola fractional derivative. The effectiveness of the theoretical results is shown through simulations for two numerical examples.