A Theory of Kernel Extreme Energy Difference for Feature Extraction of EEG Signals.
Shiliang SunJinbo LiPublished in: ADMA (2009)
Keyphrases
- eeg signals
- feature extraction
- extracted features
- feature space
- kernel density estimators
- brain computer interface
- wavelet transform
- preprocessing
- support vector
- energy consumption
- kernel methods
- pattern classification
- feature vectors
- motor imagery
- kernel principal component analysis
- pattern recognition
- discriminant analysis
- texture analysis
- kernel function
- electrical activity
- linear discriminant analysis
- neural network
- support vector machine svm
- signal processing
- multiresolution
- image processing
- data mining