Stability analysis and synchronization of incommensurate fractional-order neural netwroks
Amel Hioual, Taki-Eddine Oussaeif · 2022
This paper develops a theoretical framework for analyzing the stability of nonlinear incommensurate fractional- order neural networks. A necessary theorem for asymptotical stability is established using the characteristic equation for a nonlinear fractional-order system, and how to employ this theorem in stabilization is also presented. With the suitable control, the difficulties of stabilization and synchronization of fractional-order chaotic incommensurate fractional-order neural networks may be readily overcome. Two numerical examples have been shown to demonstrate how the established theory may be used to investigate stability and construct stabilization controllers.