Multi-scale wavelet kernel extreme learning machine for EEG feature classification
| Title | Multi-scale wavelet kernel extreme learning machine for EEG feature classification |
| Publication Type | Conference Paper |
| Year of Publication | 2015 |
| Authors | Liu, Q., Zhao, X. g, Hou, Z. g, Liu, H. g |
| Conference Name | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) |
| Date Published | jun |
| Keywords | Accuracy, Classification algorithms, EEG classification, EEG feature classification, electroencephalographic signal feature classification, electroencephalography, ELM, feature extraction, Kernel, learning (artificial intelligence), medical signal processing, multi-scale wavelet kernel, multiscale wavelet kernel extreme learning machine classifier, pubcrawl170109, signal classification, Support vector machines, Training, wavelet transforms |
| 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. |
| URL | https://ieeexplore.ieee.org/document/7288175/ |
| DOI | 10.1109/CYBER.2015.7288175 |
| Citation Key | liu_multi-scale_2015 |
- learning (artificial intelligence)
- wavelet transforms
- Training
- Support vector machines
- signal classification
- pubcrawl170109
- multiscale wavelet kernel extreme learning machine classifier
- multi-scale wavelet kernel
- medical signal processing
- Accuracy
- Kernel
- feature extraction
- ELM
- electroencephalography
- electroencephalographic signal feature classification
- EEG feature classification
- EEG classification
- Classification algorithms