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An unpredictable-dynamics approach to neural intelligence

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1 Author(s)
Zak, M. ; Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA

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.<>

Published in:

IEEE Expert  (Volume:6 ,  Issue: 4 )