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<p>The theoretical basis for a dynamic neural network architecture that takes advantage of the notion of terminal chaos to process information in a way that is phenomenologically similar to brain activity is presented. The architecture exploits the phenomenology of nonlinear dynamic systems as an alternative to the traditional paradigm of finite-state machines. It is based on some effects of nonLipschitzian dynamics. The nonlinear phenomenon of terminal chaos and its relevance to brain activity are examined.</p>

M. Zak, "An Unpredictable-Dynamics Approach to Neural Intelligence," in IEEE Intelligent Systems, vol. 6, no. , pp. 4-10, 1991.
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