TY - GEN
T1 - Properties of learning in ART1
AU - Georgiopoulos, Michael
AU - Heileman, Gregory L.
AU - Huang, Juxin
PY - 1991
Y1 - 1991
N2 - The authors consider the ART1 neural network architecture. Useful properties of ART1, associated with the learning of an arbitrary list of binary input patterns, are examined. These properties reveal some of the good characteristics of the ART1 neural network architecture when it is used as a tool for the learning of recognition categories. In particular, it was found that if ART1 is repeatedly presented with an arbitrary list of binary input patterns, learning self-stabilizes in at most m list presentations, where m corresponds to the number of distinct size patterns in the input list.
AB - The authors consider the ART1 neural network architecture. Useful properties of ART1, associated with the learning of an arbitrary list of binary input patterns, are examined. These properties reveal some of the good characteristics of the ART1 neural network architecture when it is used as a tool for the learning of recognition categories. In particular, it was found that if ART1 is repeatedly presented with an arbitrary list of binary input patterns, learning self-stabilizes in at most m list presentations, where m corresponds to the number of distinct size patterns in the input list.
UR - http://www.scopus.com/inward/record.url?scp=0026297704&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0026297704&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0026297704
SN - 0780302273
T3 - 91 IEEE Int Jt Conf Neural Networks IJCNN 91
SP - 2671
EP - 2676
BT - 91 IEEE Int Jt Conf Neural Networks IJCNN 91
PB - Publ by IEEE
T2 - 1991 IEEE International Joint Conference on Neural Networks - IJCNN '91
Y2 - 18 November 1991 through 21 November 1991
ER -