DELAY-INDUCED HOPF BIFURCATION OF A FRACTIONAL-ORDER NEURAL NETWORK WITH BOTH NEUTRAL AND INERTIAL TERMS

This paper focuses on the stability and bifurcation in a fractional-order neutral-type inertial neural network with time delay. We mainly analyze the new system with time delay by using Cramer's rule to derive precise bifurcation conditions. The accuracy of the theoretical findings is ultimately confirmed through two numerical experiments. Moreover, the remarkable advantages of the fractional-order model are found in delaying the occurrence of inherent bifurcations and enhancing the stability performance.