Generation of cyclic/toroidal chaos by Hopfield neural networks
Entrainment of limit cycles and tori by chaos in HNNs is discussed. Attraction of cyclic and toroidal chaos by an equilibrium is realized. A control technique is presented to stabilize chaotic limit cycles and tori. Simulations supporting the theoretical results are depicted. The results are not in the scope of generalized synchronization.
hopfield neural networks entrainment of limit cycles by chaos attraction of cyclic chaos by an equilibrium chaos around tori control of a chaotic torus