Title :
Classification methods using Winners-Take-All neural networks
Author_Institution :
Informational Technol. Dept., Volyn State Univ. named after Lesia Ukrainka, Lutsk, Ukraine
Abstract :
Winner-Take-All (WTA) and its extended version K-Winner-Take-All (KWTA) networks have been frequently used as the classifiers in neural networks. They are very important tools in Data mining, Machine learning and Pattern recognition. There are a lot of scientific works devoted to this technology. The elimination of limitations is main aim of the most number of these researches. KWTA is the unique strategy for solving classification problems in different branches of science. This unique character is presented in the research.
Keywords :
neural nets; pattern classification; classification methods; k-winner-take-all networks; winners-take-all neural networks; Artificial neural networks; Machine learning; Pattern classification; Pattern recognition; Prototypes; Support vector machine classification; Vectors; Classification; K-Winner-Take-All; Machine Learning; Pattern Recognition; Winner-Take-All;
Conference_Titel :
Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2011 Proceedings of VIIth International Conference on
Conference_Location :
Polyana
Print_ISBN :
978-1-4577-0639-4
Electronic_ISBN :
978-966-2191-18-9
