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Proceedings Paper

Corticonics: the way to designing machines with brainlike intelligence
Author(s): Nabil H. Farhat
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Paper Abstract

Present day neural net and connectionist models of the cortex have not been effective in duplicating higher-level brain function and specially the ability of the cortex/brain to process dynamic input patterns. Using mathematics quite- different from that used in the transfer-function and stimulus-response approach to collective nonlinear processing used in conventional networks, we describe here progress with a novel approach to modeling the cortex that combines concepts and tools from nonlinear dynamics and information theory that offers a radically new way to process, classify/learn and recognize spatio-temporal signals.

Paper Details

Date Published: 17 November 2000
PDF: 7 pages
Proc. SPIE 4109, Critical Technologies for the Future of Computing, (17 November 2000); doi: 10.1117/12.409209
Show Author Affiliations
Nabil H. Farhat, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 4109:
Critical Technologies for the Future of Computing
Sunny Bains; Leo J. Irakliotis, Editor(s)

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