DocumentCode
1680364
Title
Constrained optimization in pattern classification using ART
Author
Yang, Shuyu ; Mitra, Sunanda
Author_Institution
Dept. of Electr. & Comput. Eng., Texas Tech. Univ., Lubbock, TX, USA
Volume
3
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
2662
Lastpage
2667
Abstract
Pattern classification problems involve constrained optimization in the form of minimization of chosen cost functions. Such embedded constraints in integrated neural-fuzzy pattern recognition systems improve the performance of these systems. The comparative performance of an ART-based pattern classifier integrated with fuzzy optimization constraints is demonstrated in designing vector quantizers
Keywords
ART neural nets; constraint theory; fuzzy neural nets; minimisation; pattern classification; vector quantisation; ART neural nets; constrained optimization; embedded constraints; fuzzy optimization constraints; minimization; neural-fuzzy pattern recognition systems; pattern classification; vector quantizer design; Algorithm design and analysis; Clustering algorithms; Constraint optimization; Fuzzy logic; Neural networks; Pattern classification; Pattern recognition; Subspace constraints; Testing; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007567
Filename
1007567
Link To Document