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Proceedings Paper

Beyond Pattern Recognition With Neural Nets
Author(s): Henri H. Arsenault; Bohdan Macukow
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Paper Abstract

Neural networks are finding many areas of application. Although they are particularly well-suited for applications related to associative recall such as content-addressable memories, neural nets can perform many other applications ranging from logic operations to the solution of optimization problems. The training of a recently introduced model to perform boolean logical operations such as XOR is described. Such simple systems can be combined to perform any complex boolean operation. Any complex task consisting of parallel and serial operations including fuzzy logic that can be described in terms of input-output relations can be accomplished by combining modules such as the ones described here. The fact that some modules can carry out their functions even when their inputs contain erroneous data, and the fact that each module can carry out its functions in parallel with itself and other modules promises some interesting applications.

Paper Details

Date Published: 8 February 1989
Proc. SPIE 0960, Real-Time Signal Processing for Industrial Applications, (8 February 1989); doi: 10.1117/12.947803
Show Author Affiliations
Henri H. Arsenault, Universite Laval (Canada)
Bohdan Macukow, Universite Laval (Canada)

Published in SPIE Proceedings Vol. 0960:
Real-Time Signal Processing for Industrial Applications
Bahram Javidi, Editor(s)

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