Numerical Analysis of Bio-signal Using Generative Adversarial Networks

Material type: 文書・図像類

Author: Nakane, Kokiほか

Publisher: Springer International Publishing

Publication date: 2020

Material Format: Digital

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Note (General)：: In this decade, it is not necessary to have technical knowledge for the investment since the automatic algorithms to sell/buy investment destination h...

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Material Type: 文書・図像類
Title: Numerical Analysis of Bio-signal Using Generative Adversarial Networks
Author/Editor: Nakane, Koki
Takada, Hiroki
Yamamoto, Shota
Ono, Rentarou
Takada, Masumi
Author Heading: Nakane, Koki
Takada, Hiroki
Yamamoto, Shota
Ono, Rentarou
Takada, Masumi
Publication, Distribution, etc.: Springer International Publishing
Publication Date: 2020
Publication Date (W3CDTF): 2020
Periodical title: HCI International 2020 – Late Breaking Papers: Interaction, Knowledge and Social Media
Text Language Code: eng
Subject Heading: GAN
Double-Wayland algorithm
Stochastic process
stabilogram.
Target Audience: 一般
Note (General): In this decade, it is not necessary to have technical knowledge for the investment since the automatic algorithms to sell/buy investment destination have been developed with artificial intelligence (AI). In our previous study, measuring similarity (stationarity, fractality, and degree of determinism) of variations in the exchange rates to the pseudo-exchange rates generated by Generative Adversarial Networks (GANs), we compared Winner processes with the GANs. From the viewpoint of stationarity, the similarity of sequences in the pseudo exchange rates were higher than those generated by the Winner processes, and high scores in the similarity were resulted from both sequences in terms of degree of determinism. In this study, we have applied this AI system to numerical simulations of the stabilogram whose randomness is remarkably greater than that of the other bio-signal in accordance with the nonlinear analysis.
source:https://www.springerprofessional.de/en/numerical-analysis-of-bio-signal-using-generative-adversarial-ne/18421228
Source: https://u-fukui.repo.nii.ac.jp/?action=repository_action_common_download&item_id=28896&item_no=1&attribute_id=22&file_no=1
https://u-fukui.repo.nii.ac.jp/?action=repository_action_common_download&item_id=28896&item_no=1&attribute_id=22&file_no=1
Access Restrictions: 限定公開
Rights (production): copyright(c)Springer Fachmedien Wiesbaden GmbH
Related Material (DOI): 10.1007/978-3-030-60152-2_44
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 福井大学 : 福井大学学術機関リポジトリ