DocumentCode
2970318
Title
Determination of initial configuration for LVQ by using CNN
Author
Kim, Baek-Sop ; Lee, Sang Hee ; Kim, Dae Keuk
Author_Institution
Dept. of Comput. Sci., Hallym Univ., Chunchon, South Korea
Volume
3
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2456
Abstract
A method for determining the initial configuration for the LVQ is proposed. It is based on the condensed nearest neighbor (CNN) rule followed by the K-means clustering method. Experiments show that the proposed method is generally better than the conventional ones which use k-NN or the K-means. And it is also shown that the performance of the CNN is improved by applying the LVQ as a post processing.
Keywords
learning (artificial intelligence); neural nets; pattern recognition; vector quantisation; CNN; K-means clustering method; LVQ; condensed nearest neighbor rule; initial configuration; post processing; Bayesian methods; Cellular neural networks; Clustering algorithms; Clustering methods; Computer science; Error analysis; Nearest neighbor searches; Neural networks; Pattern recognition; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714221
Filename
714221
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