Paper
17 November 2000 Corticonics: the way to designing machines with brainlike intelligence
Nabil H. Farhat
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nabil H. Farhat "Corticonics: the way to designing machines with brainlike intelligence", Proc. SPIE 4109, Critical Technologies for the Future of Computing, (17 November 2000); https://doi.org/10.1117/12.409209
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Brain

Sensors

Functional magnetic resonance imaging

Mathematical modeling

Positron emission tomography

Signal processing

Neural networks

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