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Proceedings Paper

Neural Networks For Logic Operations
Author(s): Bohdan Macukow; Henri H. Arsenault
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Paper Abstract

A multi-layer neural networks are proposed for the implementation of general logic operations. It is shown that such systems composed of simple identical neuronlike elements can perform any Boolean function of two, three or more variables. It has to be pointed out that the learning method and thresholding function for neuronlike element are identical with previously described for content addressable memory (CAM). Interesting aspect of doing logic operations on neural networks is the ability to accomplish precise logic operations such as and, or, xor etc. on highly corrupted data.

Paper Details

Date Published: 25 October 1989
PDF: 4 pages
Proc. SPIE 1134, Optical Pattern Recognition II, (25 October 1989); doi: 10.1117/12.961612
Show Author Affiliations
Bohdan Macukow, Warsaw University of Technology (Poland)
Henri H. Arsenault, Universite Laval (Canada)

Published in SPIE Proceedings Vol. 1134:
Optical Pattern Recognition II
H. John Caulfield, Editor(s)

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