Bifurcation investigation and control scheme of fractional neural networks owning multiple delays

In this current study, novel fractional neural networks owning delay are formulated. Using Lipschitz condition, we demonstrate that the solution of the formulated fractional delayed neural networks exists and is unique. Applying a reasonable function, we handle the boundedness issue of solution to the formulated fractional delayed neural networks. Exploiting the stability criterion and bifurcation viewpoint of the fractional order delayed dynamical system, we explore the stability and bifurcation phenomenon of the established fractional delayed neural networks. Taking advantage of an adequate hybrid controller, we have efficaciously dominated the stability domain and the time of generation of bifurcation of the formulated fractional delayed neural networks. Ultimately, computer simulation graphs are provided to sustain our acquired outcomes. The acquired theoretical outcomes of this study possess considerable realistic meaning in regulating and controlling neural networks.