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Proceedings Paper

Syntactical computing using pulse-coupled neural network modules
Author(s): Jason M. Kinser
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Paper Abstract

The pulse-coupled neural network (PCNN) is a biologically motivated algorithm that has tremendous potential. The PCNN has several inherent properties that make it useful in a variety of applications. This paper introduces a syntactical information processing architecture that is mainly driven by PCNNs. It exploits several of the inherent properties of the PCNN to receive and process information, to convert the information to a syntactical phrase and its 1D form which can then be used to generate an appropriate response to the information received as an input. Examples of PCNN performance which is appropriate for this systems are given.

Paper Details

Date Published: 11 November 1996
PDF: 7 pages
Proc. SPIE 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments, (11 November 1996); doi: 10.1117/12.258120
Show Author Affiliations
Jason M. Kinser, Alabama A&M Univ. (United States)

Published in SPIE Proceedings Vol. 2824:
Adaptive Computing: Mathematical and Physical Methods for Complex Environments
H. John Caulfield; Su-Shing Chen, Editor(s)

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