Title :
Multi-scale wavelet kernel extreme learning machine for EEG feature classification
Author :
Qi Liu;Xiao-guang Zhao;Zeng-guang Hou;Hong-guang Liu
Author_Institution :
The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, CAS, Beijing, PRC
fDate :
6/1/2015 12:00:00 AM
Abstract :
In this paper, the principle of the kernel extreme learning machine (ELM) is analyzed. Based on that, we introduce a kind of multi-scale wavelet kernel extreme learning machine classifier and apply it to electroencephalographic (EEG) signal feature classification. Experiments show that our classifier achieves excellent performance.
Keywords :
"Kernel","Electroencephalography","Feature extraction","Training","Classification algorithms","Support vector machines","Accuracy"
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8728-3
DOI :
10.1109/CYBER.2015.7288175
