The proposal of the EEG characteristics extraction method in weighted principal frequency components using the RGA

Shin Ichi Ito, Yasue Mitsukura, Hiroko Nakamura Miyamura, Takafumi Saito, Minoru Fukumi

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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 are different. The real-coded genetic algorithm (: RGA) is used for selecting and being weighted the principal characteristic frequency components. We attempt to construct mental change appearance model (: MCAM) of only one measurement point. In order to show the effectiveness of the proposed method, computer simulations are carried out by using real data.

本文言語English
ホスト出版物のタイトル2006 SICE-ICASE International Joint Conference
ページ1152-1155
ページ数4
DOI
出版ステータスPublished - 2006 12月 1
外部発表はい
イベント2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
継続期間: 2006 10月 182006 10月 21

出版物シリーズ

名前2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
国/地域Korea, Republic of
CityBusan
Period06/10/1806/10/21

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 制御およびシステム工学
  • 電子工学および電気工学

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