A non-Gaussian approach for biosignal classification based on the Johnson SU translation system

Hideaki Hayashi, Yuichi Kurita, Toshio Tsuji

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

3 被引用数 (Scopus)

抄録

This paper proposes a non-Gaussian approach for biosignal classification based on the Johnson SU translation system. The Johnson system is a normalizing translation that transforms data without normality to normal distribution using four parameters, thereby enabling the representation of a wide range of shapes for marginal distribution with skewness and kurtosis. In this study, a discriminative model based on the multivariate Johnson SU translation system is transformed into linear combinations of coefficients and input vectors using log-linearization, and is incorporated into a neural network structure, thereby allowing the determination of model parameters as weight coefficients of the network via backpropagation-based training. In the experiments, the classification performance of the proposed network is demonstrated using artificial data and electromyogram data.

本文言語英語
ホスト出版物のタイトル2015 IEEE 8th International Workshop on Computational Intelligence and Applications, IWCIA 2015 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ115-120
ページ数6
ISBN(電子版)9781479998869
DOI
出版ステータス出版済み - 4月 7 2016
外部発表はい
イベント8th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2015 - Hiroshima, 日本
継続期間: 11月 6 201511月 7 2015

出版物シリーズ

名前2015 IEEE 8th International Workshop on Computational Intelligence and Applications, IWCIA 2015 - Proceedings

その他

その他8th IEEE International Workshop on Computational Intelligence and Applications, IWCIA 2015
国/地域日本
CityHiroshima
Period11/6/1511/7/15

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ ビジョンおよびパターン認識
  • 制御と最適化
  • 人工知能
  • コンピュータ サイエンスの応用

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