Dynamic Analysis of Fractional-Order Recurrent Neural Network with Caputo Derivative

Abstract

In this paper, fractional-order recurrent neural network models with Caputo Derivative are investigated. Firstly, we mainly focus our attention on Hopf bifurcation conditions for commensurate fractional-order network with time delay to reveal the essence that fractional-order equation can simulate the activity of neuron oscillation. Secondly, for incommensurate fractional-order neural network model, we prove the stability of the zero equilibrium point to show that incommensurate fractional-order neural network still converges to zero point. Finally, Hopf bifurcation conditions for the incommensurate fractional-order neural network model are first obtained using bifurcation theory based on commensurate fractional-order system.