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Stability, bifurcation analysis in a neural network model with delay and diffusion
We consider a delayed neural network model with diffusion. By analyzing the
distributions of the eigenvalues of the system and applying the center
manifold theory and normal form computation, we show
that, regarding the connection coefficients as the perturbation parameter,
the system, with the different boundary conditions, undergoes some bifurcations
including transcritical bifurcation, Hopf bifurcation and Hopf-zero bifurcation.
The normal forms are given to determine the stabilities of the bifurcated
solutions.