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Hierarchical structure of deterministic chaos in a chaotic neural network model (CNN) is investigated in the view of application in robotics. The result shows a rich capacity of CNN in selectively controlling the synchronization of neuron outputs, and sensitively responding to external sensory inputs, both being based on the intrinsic mechanism of the dynamics called chaotic itinerancy. Choosing appropriate...
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