DocumentCode
313624
Title
Competitive and hybrid neuro-fuzzy models for supervised classification
Author
Giusti, Nicola ; Sperduti, Alessandro ; Masulli, Francesco
Author_Institution
Dipt. di Inf., Pisa Univ., Italy
Volume
1
fYear
1997
fDate
9-12 Jun 1997
Firstpage
516
Abstract
Neuro-fuzzy systems are often very complex and may require long training times. In the context of supervised classification, we propose a competitive and a hybrid model based on fuzzy basis function networks. These models are fast to train and still hold very good generalization performances. Experimental results on the classification of handwritten digits are presented
Keywords
competitive algorithms; fuzzy neural nets; generalisation (artificial intelligence); pattern classification; competitive neuro-fuzzy models; fuzzy basis function networks; handwritten digits; hybrid neuro-fuzzy models; supervised classification; Context modeling; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Gravity; MIMO; Parameter estimation; Shape; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.611722
Filename
611722
Link To Document