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  Frequency Peak Features for Low-Channel Classification in Motor Imagery Paradigms

Jayaram, V., Schölkopf, B., & Grosse-Wentrup, M. (2017). Frequency Peak Features for Low-Channel Classification in Motor Imagery Paradigms. In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER 2017) (pp. 321-324). Piscataway, NJ: IEEE. doi:10.1109/NER.2017.8008355.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000A-ABC3-9 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-ABC4-8
Genre: Conference Paper

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 Creators:
Jayaram, Vinay1, Author
Schölkopf, Bernhard2, Author           
Grosse-Wentrup, Moritz2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
 Abstract: -

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Language(s): eng - English
 Dates: 2017-08-152017
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/NER.2017.8008355
BibTex Citekey: JaySchGro17
 Degree: -

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Title: 8th International IEEE/EMBS Conference on Neural Engineering (NER 2017)
Place of Event: Shanghai
Start-/End Date: 2017-08-25 - 2017-08-28

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Title: 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER 2017)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 321 - 324 Identifier: ISBN: 978-1-5090-4603-4
ISBN: 978-1-5090-4604-1
ISSN: 1948-3554
ISSN: 1948-3546
DOI: 10.1109/NER36745.2017