Beyond Pattern Recognition With Neural Nets

Henri H. Arsenault; Bohdan Macukow

doi:10.1117/12.947803

8 February 1989 Beyond Pattern Recognition With Neural Nets

Henri H. Arsenault, Bohdan Macukow

Proceedings Volume 0960, Real-Time Signal Processing for Industrial Applications; (1989) https://doi.org/10.1117/12.947803
Event: SPIE International Symposium on Optical Engineering and Industrial Sensing for Advance Manufacturing Technologies, 1988, Dearborn, MI, United States

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.

Citation Download Citation

Henri H. Arsenault and Bohdan Macukow "Beyond Pattern Recognition With Neural Nets", Proc. SPIE 0960, Real-Time Signal Processing for Industrial Applications, (8 February 1989); https://doi.org/10.1117/12.947803

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