Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis

Nagai, Kotaro; Kanemoto, Daisuke; Ohki, Makoto

doi:https://doi.org/10.1587/transfun.2020EAL2123

Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis

Nagai, Kotaro; Kanemoto, Daisuke; Ohki, Makoto

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2021, E104A(9), 1375-1378

アクセス数:311件（2025-11-25 02:00 集計）

固定URL: https://hdl.handle.net/11094/97770

閲覧可能ファイル

ファイル	フォーマット	利用条件	サイズ	閲覧回数	利用開始日	説明	information
IEICETransFundElecComSci_E104A_9_1375	pdf	なし	408 KB	61	2024.08.29

論文情報

ファイル出力 EndNote Basic出力 Mendeley出力

タイトル	Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis
著者	著者名 Nagai, Kotaro
	NRID 1000090603332 1000090603332 researchmap permalink dkanemoto dkanemoto Scopus Author ID 6504308983 6504308983 ORCID 0009-0002-7564-6351 0009-0002-7564-6351 著者名 Kanemoto, Daisuke
	NRID 1000050211785 1000050211785 著者名 Ohki, Makoto
キーワード等	Compressed sensing
	EEG
	Independent component analysis
	K-SVD dictionary learning
	Outlier detection
内容	Nagai K., Kanemoto D., Ohki M.. Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E104A, 1375 (2021); https://doi.org/10.1587/transfun.2020EAL2123.
抄録	This letter reports on the effectiveness of applying the K-singular value decomposition (SVD) dictionary learning to the electroencephalogram (EEG) compressed sensing framework with outlier detection and independent component analysis. Using the K-SVD dictionary matrix with our design parameter optimization, for example, at compression ratio of four, we improved the normalized mean square error value by 31.4% compared with that of the discrete cosine transform dictionary for CHB-MIT Scalp EEG Database.
出版者	電子情報通信学会
出版者	Institute of Electronics Information Communication Engineers
収録物名	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
巻(号)	E104A(9)
ページ	1375-1378
刊行年月	2021-09-01
言語	英語
ハンドルURL	https://hdl.handle.net/11094/97770
PISSN	09168508
eISSN	17451337
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1587/transfun.2020EAL2123
アクセス権	open access
権利情報	Copyright © 2021 The Institute of Electronics, Information and Communication Engineers
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCTERMS.bibliographicCitation	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2021, E104A(9), p. 1375-1378
DC.title	Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis
DC.creator	Nagai, Kotaro
	Kanemoto, Daisuke
	Ohki, Makoto
DC.publisher	電子情報通信学会
DC.publisher	Institute of Electronics Information Communication Engineers
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2021-09-01
DC.identifier	https://doi.org/10.1587/transfun.2020EAL2123
DC.subject	Compressed sensing
	EEG
	Independent component analysis
	K-SVD dictionary learning
	Outlier detection
DC.description	Nagai K., Kanemoto D., Ohki M.. Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E104A, 1375 (2021); https://doi.org/10.1587/transfun.2020EAL2123.
DCTERMS.abstract	This letter reports on the effectiveness of applying the K-singular value decomposition (SVD) dictionary learning to the electroencephalogram (EEG) compressed sensing framework with outlier detection and independent component analysis. Using the K-SVD dictionary matrix with our design parameter optimization, for example, at compression ratio of four, we improved the normalized mean square error value by 31.4% compared with that of the discrete cosine transform dictionary for CHB-MIT Scalp EEG Database.
DC.rights	Copyright © 2021 The Institute of Electronics, Information and Communication Engineers
DC.format	97770
citation_title	Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis
citation_author	Nagai, Kotaro
	Kanemoto, Daisuke
	Ohki, Makoto
citation_publisher	電子情報通信学会
citation_language	英語
citation_date	2021-09-01
citation_journal_title	IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
citation_volume	E104A
citation_issue	9
citation_firstpage	1375
citation_lastpage	1378
citation_doi	https://doi.org/10.1587/transfun.2020EAL2123
citation_public_url	https://hdl.handle.net/11094/97770

Applying K-SVD dictionary learning for EEG compressed sensing framework with outlier detection and independent component analysis

閲覧可能ファイル

論文情報

論文詳細を表示