An Efficient Self-Organizing Map Learning Algorithm with Winning Frequency of Neurons for Clustering Application

被引：0

作者：

Chaudhary, Vikas ^{[1
]}

Ahlawat, Anil K. ^{[2
]}

Bhatia, R. S. ^{[1
]}

机构：

[1] Natl Inst Technol NIT, Kurukshetra, Haryana, India

[2] Krishna Inst Engn & Technol, Dept Comp Applicat, Ghaziabad, Uttar Pradesh, India

来源：

PROCEEDINGS OF THE 2013 3RD IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC) | 2013年

关键词：

Self-organizing map (SOM); winning frequency; modified SOM;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

u The Self-organizing map (SOM) has been extensively applied to data clustering, image analysis, dimension reduction, and so forth. The conventional SOM does not calculate the winning frequency of each neuron. In this study, we propose a modified SOM which calculate the winning frequency of each neuron. We investigate the behavior of modified SOM in detail. The learning performance is evaluated using the three measurements. We apply modified SOM to various input data set and confirm that modified SOM obtain a more effective map reflecting the distribution state of the input data.

引用

页码：672 / 676

页数：5

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