TY - GEN
T1 - A new on-line self-constructing neural fuzzy network
AU - Ferreyra, Andrés
AU - De Jesús Rubio, José
PY - 2006
Y1 - 2006
N2 - In this paper, we propose a new on-line self-constructing neural fuzzy network. Structure and parameter learning are updated at the same time in our algorithm, because there is no difference between them. It generates groups with a given radius. The center is updated in order to get a nearest one to the incoming data in each iteration, in this way, it does not generate many rules and it does not need to prune them. We give a time varying learning rate for backpropagation training. We use extended Kalman filter to train the center of sets in the THEN part. We proved the stability in both cases.
AB - In this paper, we propose a new on-line self-constructing neural fuzzy network. Structure and parameter learning are updated at the same time in our algorithm, because there is no difference between them. It generates groups with a given radius. The center is updated in order to get a nearest one to the incoming data in each iteration, in this way, it does not generate many rules and it does not need to prune them. We give a time varying learning rate for backpropagation training. We use extended Kalman filter to train the center of sets in the THEN part. We proved the stability in both cases.
UR - http://www.scopus.com/inward/record.url?scp=39649119442&partnerID=8YFLogxK
U2 - 10.1109/cdc.2006.377770
DO - 10.1109/cdc.2006.377770
M3 - Contribución a la conferencia
AN - SCOPUS:39649119442
SN - 1424401712
SN - 9781424401710
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3003
EP - 3009
BT - Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 45th IEEE Conference on Decision and Control 2006, CDC
Y2 - 13 December 2006 through 15 December 2006
ER -