Dynamic behavior of high-dimensional heterogeneous fractional-order neural networks with multiple delays

In this paper, we study the stability and bifurcation of a class of high-dimensional heterogeneous fractional-order neural networks with multiple delays. Firstly, taking the time delay as the bifurcation parameter, the dynamic behavior including stability and Hopf bifurcation is discussed, and the conditions for the bifurcation are obtained. Secondly, fixing one kind of delay, we further discuss the influence on the bifurcation point of another kind of delay. Then, the influence of heterogeneous fractional-order on bifurcation point is discussed. The results show that the proper change of order can obviously advance the start of bifurcation. Finally, two numerical examples are used to verify the validity of the theoretical results.