A Novel Mutual-Information-Guided Sparse Feature Selection Approach for Epilepsy Diagnosis Using Interictal EEG Signals.
Shouyi WangCao XiaoJeffrey J. TsaiWanpracha Art ChaovalitwongseThomas J. GrabowskiPublished in: BIH (2016)
Keyphrases
- eeg signals
- mutual information
- feature selection
- obstructive sleep apnea
- conditional mutual information
- information theoretic
- signal processing
- information gain
- image registration
- healthy subjects
- brain computer interface
- similarity measure
- brain activity
- sparse pca
- support vector machine
- text categorization
- linear discriminant classifier
- high dimensional
- classification accuracy
- feature space
- feature selection algorithms
- kernel density estimators
- parzen window
- event related potentials
- motor imagery
- image processing
- feature set
- knn
- pattern recognition
- eeg data
- feature subset
- electrical activity
- brain signals
- naive bayes
- image analysis
- support vector