Bifurcation analysis and control of delayed neural network model with two-neurons
Cong Chen · Control theory & applications · 2003
The nonlinear behavior in a delayed neural network model with two neurons is investigated. Conditions from stability to bifurcation of the model are presented by applying the linear stability theory. The analytical mechanism for the beginning of cyclic behavior is based on a Hopf_type bifurcation theory. The bifurcation and amplitude of the bifurcated solution are proved to be controlled by utilizing bifurcation stability conefficients can control bifurcation. An example is given and numerical simulations are performed to illustrate the results.\;