Automatic EEG artifact removal: A weighted support vector machine approach with error correction
10.1109/TBME.2008.2005969
Saved in:
Main Authors: | Shao, S.-Y., Shen, K.-Q., Ong, C.J., Wilder-Smith, E.P.V., Li, X.-P. |
---|---|
Other Authors: | MECHANICAL ENGINEERING |
Format: | Article |
Published: |
2011
|
Subjects: | |
Online Access: | http://scholarbank.nus.edu.sg/handle/10635/27049 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Automatic identification and removal of artifacts in EEG using a probabilistic multi-class SVM approach with error correction
by: Shao, S.-Y., et al.
Published: (2014) -
EEG-based mental fatigue measurement using multi-class support vector machines with confidence estimate
by: Shen, K.-Q., et al.
Published: (2011) -
H∞ adaptive filters for eye blink artifact minimization from electroencephalogram
by: Puthusserypady, S., et al.
Published: (2014) -
Detection and removal of lighting & shaking artifacts in home videos
by: Yan, W.-Q., et al.
Published: (2014) -
Detection and removal of lighting & shaking artifacts in home videos
by: Yan, W.-Q., et al.
Published: (2013)