Destructive Fuzzy Modeling Using Neural Gas Network

Kazuya KISHIDA  Hiromi MIYAJIMA  Michiharu MAEDA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A   No.9   pp.1578-1584
Publication Date: 1997/09/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)
Category: 
Keyword: 
fuzzy model,  destructive method,  neural-gas network,  descent method,  vector quantization,  

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Summary: 
In order to construct fuzzy systems automatically, there are many studies on combining fuzzy inference with neural networks. In these studies, fuzzy models using self-organization and vector quantization have been proposed. It is well known that these models construct fuzzy inference rules effectively representing distribution of input data, and not affected by increment of input dimensions. In this paper, we propose a destructive fuzzy modeling using neural gas network and demonstrate the validity of a proposed method by performing some numerical examples.