Presentation 2006/6/29
The Proposal of the Feature Extraction Method in Weighted Principal Frequency Components Using the RGA
Shin-ichi ITO, Yasue MITSUKURA, Nakamura Hiroko MIYAMURA, Takafumi SAITO, Minoru FUKUMI,
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Abstract(in English) An EEG has frequency components which can describe most of the significant features. These combinations are often unique like individual human beings and yet they have underlying basic features. These frequency components are contained the important and/or not so important components, and then each importance of these frequency components is different. The real-coded genetic algorithm (: RGA) is used for selecting and weighting the principal characteristic frequency components. We attempt to construct mental change appearance model (: MCAM) of one measurement point only. In order to show the effectiveness of the proposal method, computer simulations are carried out by using real data.
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Keyword(in English) Electroencephalogram / Real-coded Genetic Algorithms / Structure Equation Model / Mental Change
Paper # HIP2006-37
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Committee HIP
Conference Date 2006/6/29(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) The Proposal of the Feature Extraction Method in Weighted Principal Frequency Components Using the RGA
Sub Title (in English)
Keyword(1) Electroencephalogram
Keyword(2) Real-coded Genetic Algorithms
Keyword(3) Structure Equation Model
Keyword(4) Mental Change
1st Author's Name Shin-ichi ITO
1st Author's Affiliation Graduate School of Bio-Applications & Systems Engineering, Tokyo University of Agriculture and Technology()
2nd Author's Name Yasue MITSUKURA
2nd Author's Affiliation Graduate School of Bio-Applications & Systems Engineering, Tokyo University of Agriculture and Technology
3rd Author's Name Nakamura Hiroko MIYAMURA
3rd Author's Affiliation Graduate School of Bio-Applications & Systems Engineering, Tokyo University of Agriculture and Technology
4th Author's Name Takafumi SAITO
4th Author's Affiliation Graduate School of Bio-Applications & Systems Engineering, Tokyo University of Agriculture and Technology
5th Author's Name Minoru FUKUMI
5th Author's Affiliation Department of Information Science & Intelligent System, Faculty of Engineering University of Tokushima
Date 2006/6/29
Paper # HIP2006-37
Volume (vol) vol.106
Number (no) 143
Page pp.pp.-
#Pages 6
Date of Issue