By Topic

A new approach to the design of neural network classifiers and its application to the automatic recognition of handwritten digits

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
S. Knerr ; Lab. d'Electron., Ecole Superieure de Phys. et de Chimie Industrielles de la Ville de Paris, France ; L. Personnaz ; G. Dreyfus

Describes a procedure for simultaneously building and training a neural network. Its salient features are the following: (1) the resulting network uses neurons with binary outputs, which makes hardware implementations straightforward; (2) the network has one single layer of trainable connections, therefore, training is fast; (3) the additional layers perform explicit Boolean functions, therefore these layers require no training and they can be implemented in hardware with standard logic gates; and (4) the procedure gives insight into the complexity of the problem. The application of this procedure to the recognition of handwritten digits is presented. The structure of an application-specific integrated circuit, which is in the design phase, is briefly described

Published in:

Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on  (Volume:i )

Date of Conference:

8-14 Jul 1991