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Stability analysis of nonlinear neural network models

The problem of stability for nonlinear neural networks is addressed in this paper. By means of the Lyapunov function of Lurie type, new classes of stability conditions for general neural network models are presented. The stability analysis here is global in the space of neuronal activations. An illustrated example is given.