Presentation	2008-02-01 Neural Gas Containing Two Kinds of Neurons and its Behaviors Keiko KANDA, Haruna MATSUSHITA, Yoshifumi NISHIO,
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Abstract(in English)	In this study, we propose two new Neural Gas algorithms. One method is the Neural Gas Containing Two Kinds of Neurons (called TN-NG). In TN-NG, all neurons learn according to own character at each learning. The other method is the Neural Gas Containing Two Kinds of Update Functions (called TF-NG). In TF-NG, all neurons learn according to winner's character at each learning. The behavior of TN-NG and TF-NG is investigated with computer simulation. We confirm that TN-NG and TF-NG can obtain the more effective learning results than the conventional Neural Gas.
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Keyword(in English)	neural gas / feature extraction / noise reduction
Paper #	NLP2007-143
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Conference Information
Committee	NLP
Conference Date	2008/1/25(1days)
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Paper Information
Registration To	Nonlinear Problems (NLP)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Neural Gas Containing Two Kinds of Neurons and its Behaviors
Sub Title (in English)
Keyword(1)	neural gas
Keyword(2)	feature extraction
Keyword(3)	noise reduction
1st Author's Name	Keiko KANDA
1st Author's Affiliation	Department of Electrical and Electronic Engineering, Tokushima University()
2nd Author's Name	Haruna MATSUSHITA
2nd Author's Affiliation	Department of Electrical and Electronic Engineering, Tokushima University
3rd Author's Name	Yoshifumi NISHIO
3rd Author's Affiliation	Department of Electrical and Electronic Engineering, Tokushima University
Date	2008-02-01
Paper #	NLP2007-143
Volume (vol)	vol.107
Number (no)	478
Page	pp.pp.-
#Pages	4
Date of Issue