DocumentCode
2737874
Title
Competitive Hebbian learning
Author
White, R.H.
Author_Institution
Dept. of Phys. & Comput. Sci., San Diego Univ., CA
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given. Competitive Hebbian learning, a modified Hebbian-learning rule, is introduced. In competitive Hebbian learning the change in each connection weight is made proportional to the product of node and input activities multiplied by a factor which decreases with increasing activity on the other nodes. The individual nodes learn to respond to different components of the input activity while collectively developing maximal response. Several applications of competitive Hebbian learning were presented to show examples of the power and versatility of this learning algorithm
Keywords
learning systems; neural nets; competitive Hebbian learning; connection weight; input activities; input activity; maximal response; modified Hebbian-learning rule; Application software; Computer science; Hebbian theory; Physics; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155554
Filename
155554
Link To Document