Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications
The optimization of peak detection algorithms for electroencephalogram (EEG) signal analysis is an ongoing project; previously existing algorithms have been used with different models to detect EEG peaks in various applications. However, none of the existing techniques perform adequately in eye even...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Published: |
Springer India
2017
|
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12046-017-0633-9 https://doi.org/10.1007/s12046-017-0633-9 http://umpir.ump.edu.my/17480/1/Improving%20EEG%20signal%20peak%20detection%20using%20feature%20weight%20learning%20of%20a%20neural%20network%20with%20random%20weights%20for%20eye%20event-related%20applications.pdf http://umpir.ump.edu.my/17480/3/Improving%20EEG%20signal%20peak%20detection%20using%20feature%20weight%20learning%20of%20a%20neural%20network%20with%20random%20weights%20for%20eye%20event-related%20applications%201.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Internet
https://doi.org/10.1007/s12046-017-0633-9https://doi.org/10.1007/s12046-017-0633-9
http://umpir.ump.edu.my/17480/1/Improving%20EEG%20signal%20peak%20detection%20using%20feature%20weight%20learning%20of%20a%20neural%20network%20with%20random%20weights%20for%20eye%20event-related%20applications.pdf
http://umpir.ump.edu.my/17480/3/Improving%20EEG%20signal%20peak%20detection%20using%20feature%20weight%20learning%20of%20a%20neural%20network%20with%20random%20weights%20for%20eye%20event-related%20applications%201.pdf