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 -