Neural Networks For Logic Operations

Bohdan Macukow; Henri H. Arsenault

doi:10.1117/12.961612

25 October 1989 Neural Networks For Logic Operations

Bohdan Macukow, Henri H. Arsenault

Proceedings Volume 1134, Optical Pattern Recognition II; (1989) https://doi.org/10.1117/12.961612
Event: 1989 International Congress on Optical Science and Engineering, 1989, Paris, France

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.

Citation Download Citation

Bohdan Macukow and Henri H. Arsenault "Neural Networks For Logic Operations", Proc. SPIE 1134, Optical Pattern Recognition II, (25 October 1989); https://doi.org/10.1117/12.961612

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available