Motor-Imagery Classification Using Riemannian Geometry with Median Absolute Deviation

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Veröffentlicht in:Electronics Jg. 9; S. 1584
Hauptverfasser: Abu Saleh Musa Miah, Abdur Rahim, Jungpil Shin
Format: Journal Article
Sprache:Japanisch
Veröffentlicht: MDPI AG 27.09.2020
Schlagworte:
Artificial intelligence
Biology
Brain-Computer Interfaces
Brain-Computer Interfaces in Neuroscience and Medicine
brain–computer interface
Cellular and Molecular Neuroscience
Cognitive Neuroscience
Computer science
Context (archaeology)
Covariance
electroencephalogram (EEG)
Electroencephalography
Eye Movement Analysis
Eye Tracking in Human-Computer Interaction
Feature extraction
FOS: Mathematics
FOS: Psychology
Head Gesture Recognition
Human-Computer Interaction
Life Sciences
linear discriminant analysis
Mathematics
median absolute deviation
motor imagery
Neural Interface Technology
Neuroscience
Paleontology
Pattern recognition (psychology)
Physical Sciences
Principal component analysis
Psychiatry
Psychology
Quadratic classifier
Riemannian geometry
Statistics
Support vector machine
ISSN:2079-9292
Online-Zugang:Volltext
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ISSN:2079-9292
DOI:10.3390/electronics9101584