By Topic

A study of extended learning strategies for bidirectional associative memories

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

1 Author(s)
A. Neubauer ; Dept. of Commun. Eng., Duisburg Gerhard-Mercator-Univ., Duisburg

This paper presents a study of extended learning mechanisms for Kosko's bidirectional associative memory-a classical artificial neural network with applications to, for example, pattern recognition and image processing. The incorporation of sigma-pi (ΣΠ)-units instead of the conventional Σ-units in the BAM is considered leading to the ΣΠ-BAM. A Hebbian learning algorithm for ΣΠ-units is proposed and simulation results are given, indicating the increased performance of the ΣΠ-BAM as a pattern association device

Published in:

Neural Networks, 1995. Proceedings., IEEE International Conference on  (Volume:4 )

Date of Conference:

Nov/Dec 1995