Abstract
Failure of the Lipschitz condition in unstable equilibrium points of dynamical systems leads to a multiple-choice response to an initial deterministic input. The evolution of such systems is characterized by a special type of unpredictability measured by unbounded Lyapunov exponents. Possible relation of these systems to future neural networks is discussed.
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