Learning suite of kernel feature spaces enhances SMR-based EEG-BCI classification.
Berdakh AbibullaevPublished in: BCI (2017)
Keyphrases
- feature space
- motor imagery
- supervised learning
- brain computer interface
- feature vectors
- decision trees
- unsupervised learning
- training samples
- learning algorithm
- signal processing
- online training
- learning problems
- learning process
- pattern recognition
- active learning
- reinforcement learning
- eeg data
- image representation
- kernel learning
- support vector
- incremental learning
- single trial
- feature extraction
- high dimensional feature space
- extracted features
- kernel methods
- class labels
- training set
- high dimensional
- machine learning
- dimensionality reduction
- classification accuracy