Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection.
Boualem BoashashGhasem AzemiNabeel Ali KhanPublished in: Pattern Recognit. (2015)
Keyphrases
- change detection
- non stationary
- abnormality detection
- signal analysis
- empirical mode decomposition
- feature extraction
- signal processing
- instantaneous frequency
- eeg data
- eeg signals
- blind source separation
- biomedical signals
- remote sensing
- image processing
- remote sensing images
- pattern recognition
- data streams
- hilbert transform
- wavelet transform
- brain computer interface
- satellite images
- physiological signals
- frequency domain
- image registration
- independent component analysis
- multiresolution
- wavelet packet
- concept drift
- autoregressive
- multispectral
- data sets
- computational complexity
- extracted features
- frequency modulation