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pro vyhledávání: '"eigenface analysis"'
Akademický článek
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Publikováno v:
Applied Sciences, Vol 14, Iss 21, p 10062 (2024)
This study is intended to improve the motor imagery classification performance of two-class data points using newly developed covariance decentering eigenface analysis (CDC-EFA). When extracting the classification for the given data points, it is nec
Externí odkaz:
https://doaj.org/article/2a4fb7fb8c254eb890f56e36baf42e05
Autor:
Choi, Hojong1 (AUTHOR), Park, Junghun2 (AUTHOR), Yang, Yeon-Mo2 (AUTHOR) yangym@vivaldi.kumoh.ac.kr
Publikováno v:
Sensors (14248220). Aug2022, Vol. 22 Issue 15, p5860-N.PAG. 18p.
Publikováno v:
Sensors, Vol 22, Iss 15, p 5860 (2022)
The brain–computer interface (BCI) is used to understand brain activities and external bodies with the help of the motor imagery (MI). As of today, the classification results for EEG 4 class BCI competition dataset have been improved to provide bet
Externí odkaz:
https://doaj.org/article/53280119844641ccb3940eb8474b1e43
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 33:60-65
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1f5f9a386a430e7d7164645812d9062
https://doi.org/10.5391/jkiis.2023.33.1.60
https://doi.org/10.5391/jkiis.2023.33.1.60
Autor:
Choi, Hojong1 (AUTHOR), Park, Junghun2 (AUTHOR), Yang, Yeon-Mo2 (AUTHOR) yangym@vivaldi.kumoh.ac.kr
Publikováno v:
Sensors (14248220). Aug2022, Vol. 22 Issue 16, p6042-6042. 18p.
Publikováno v:
International Journal of Telemedicine and Clinical Practices. 2:148
This paper proposes a novel feature extraction scheme utilising an Eigenface analysis (EFA) algorithm for a brain computer interface (BCI). In EFA, the obtained BCI data is systematically rearranged into time, channels, and trials to develop neuro-im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49e2e672f8006fc3482fe7bf0de8ca6e
https://doi.org/10.1504/ijtmcp.2017.083887
https://doi.org/10.1504/ijtmcp.2017.083887
Publikováno v:
Sensors, Vol 22, Iss 16, p 6042 (2022)
A novel whitening technique for motor imagery (MI) classification is proposed to reduce the accuracy variance of brain–computer interfaces (BCIs). This method is intended to improve the electroencephalogram eigenface analysis performance for the MI
Externí odkaz:
https://doaj.org/article/5086d53013c549fda6c00b9242566301
Autor:
Lee, Suk-Ho1 (AUTHOR) dkkang@dongseo.ac.kr, Kang, Dae-Ki1 (AUTHOR)
Publikováno v:
Sensors (14248220). Aug2024, Vol. 24 Issue 16, p5130. 4p.
Publikováno v:
Sensors (14248220). Dec2023, Vol. 23 Issue 23, p9493. 13p.