Feature Selection of Multichannel EEG for Attention Classification.
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| Title: | Feature Selection of Multichannel EEG for Attention Classification. |
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| Authors: | Nugroho, Atmoko1,2, atmoko@usm.ac.id, Manongga, Danny1, danny.manongga@uksw.edu, Purnomo, Hindriyanto Dwi1, hindriyanto.purnomo@uksw.edu, Hendry, Hendry1, hendry@uksw.edu |
| Source: | Engineering, Technology & Applied Science Research; Feb2026, Vol. 16 Issue 1, p32544-32549, 6p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 192212732 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192212732 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48084/etasr.13062 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 32544 Titles: – TitleFull: Feature Selection of Multichannel EEG for Attention Classification. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Nugroho, Atmoko – PersonEntity: Name: NameFull: Manongga, Danny – PersonEntity: Name: NameFull: Purnomo, Hindriyanto Dwi – PersonEntity: Name: NameFull: Hendry, Hendry IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 22414487 Numbering: – Type: volume Value: 16 – Type: issue Value: 1 Titles: – TitleFull: Engineering, Technology & Applied Science Research Type: main |
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