A real-time neuro-adaptive controller with guaranteed stability
Applied Soft Computing
A study of the transiently chaotic neural network for combinatorial optimization
Mathematical and Computer Modelling: An International Journal
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The author analyzes the number, location, and stability behavior of the equilibria of arbitrary nonlinear neural networks without resorting to energy arguments based on assumptions of symmetric interactions or no self-interactions. The class of networks studied consists of very general continuous-time continuous-state (CTCS) networks that contain the standard Hopfield network as a special case. The emphasis is on the case where the slopes of the sigmoidal nonlinearities become larger and larger