Title :
Competitive Hebbian learning
Author_Institution :
Dept. of Phys. & Comput. Sci., San Diego Univ., CA
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;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155554
