&lt;title&gt;Kohonen self-organizing feature map and its use in clustering&lt;/title&gt;

Markus Torma,Heinrich Ebner,Christian Heipke,Konrad Eder

doi:10.1117/12.182900

<title>Kohonen self-organizing feature map and its use in clustering</title>

Markus Torma, Heinrich Ebner + Show 2 more

https://doi.org/10.1117/12.182900

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Publication Date: Aug 17, 1994

Citations: 7

#Kohonen Self-organizing Feature Map #Kohonen Self + Show 8 more

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Abstract

Cluster analysis is an important part of pattern recognition. In this paper we present the applicability of one neural network model, namely Kohonen self-organizing feature map, to cluster analysis. The aim is to develop a method which could determine the correct number of clusters by itself. First, the general concept of neural networks and detailed introduction to Kohonen self-organizing feature map are discussed. Then, the suitability of Kohonen self- organizing feature map to cluster analysis is discussed and some simulations are presented.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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