EEG signal classification of imagined speech based on Riemannian distance of correntropy spectral density.
Mohamad Amin BakhshaliMorteza KhademiAbbas Ebrahimi-MoghadamSahar MoghimiPublished in: Biomed. Signal Process. Control. (2020)
Keyphrases
- positive and negative
- eeg signals
- extracted features
- eeg data
- spectral density
- machine learning
- support vector
- speech recognition
- classification accuracy
- pattern recognition
- computer vision
- feature space
- support vector machine
- feature vectors
- motor imagery
- training set
- brain computer interface
- face recognition
- kernel density estimators
- decision trees
- feature extraction
- signal processing
- distance transform
- manifold learning
- pattern classification
- tensor field
- texture analysis
- quadratic optimization
- obstructive sleep apnea
- euclidean distance