By Topic

An implementation and evaluation of the ART1 neural network for pattern recognition

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
$31 $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

1 Author(s)
Albright, J.P. ; Southern Coll. of Technol., Marietta, GA, USA

A key to solving the stability-plasticity dilemma is to add a feedback mechanism between the competitive and the input layer of a network. This feedback mechanism facilitates the learning of new information without destroying old information, automatic switching between stable and plastic modes, and stabilization of the encoding of the classes done by the nodes resulting from this approach we have a neural network architecture that is particularly suited for pattern-classification problems in real world environments. For industrial use, ART1 neural networks have the potential of becoming an important component in a variety of commercial and military systems. Efficient software emulations of these networks are adequate in many of today's low-end applications such as information retrieval or group technology; but for larger applications, special purpose hardware is required to achieve the expected performance requirements

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:1 )

Date of Conference:

27 Jun-2 Jul 1994