Deep Principal Component Analysis Based on Layerwise Feature Extraction and Its Application to Nonlinear Process Monitoring.
Xiaogang DengXuemin TianSheng ChenChris J. HarrisPublished in: IEEE Trans. Control. Syst. Technol. (2019)
Keyphrases
- principal component analysis
- feature extraction
- kernel principal component analysis
- kernel pca
- dimension reduction
- dimensionality reduction
- principal components
- linear discriminant analysis
- face recognition
- discriminant analysis
- feature space
- independent component analysis
- face images
- image classification
- neural classifier
- feature vectors
- low dimensional
- independent components analysis
- covariance matrix
- texture features
- image processing
- training procedure
- face databases
- texture classification
- feature selection
- dimension reduction methods
- feature extraction and classification
- high dimensional feature space
- lower dimensional
- preprocessing
- pattern classification
- wavelet transform
- feature set
- support vector machine svm
- extracted features
- gabor filters
- nonlinear functions
- gabor wavelets
- pattern recognition
- dimensionality reduction methods
- manifold learning
- multiscale
- linear feature extraction