Feature Optimize and Classification of EEG Signals: Application to Lie Detection Using KPCA and ELM
EEG signals had been widely used to detect liars recent years. To overcome the shortcomings of current signals processing, kernel principal component analysis (KPCA) and extreme learning machine (ELM) was combined to detect liars. We recorded the EEG signals at Pz from 30 randomly divided guilty and...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IFSA Publishing, S.L.
2014-04-01
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| Series: | Sensors & Transducers |
| Subjects: | |
| Online Access: | http://www.sensorsportal.com/HTML/DIGEST/april_2014/Vol_169/P_RP_0109.pdf |