Principal component analysis for errors-in-variables subspace identification.
Jin WangS. Joe QinPublished in: CDC (2001)
Keyphrases
- principal component analysis
- principal components
- dimensionality reduction
- low dimensional
- dimension reduction
- subspace learning
- independent component analysis
- feature extraction
- lower dimensional
- face recognition
- variable selection
- feature space
- covariance matrix
- negative matrix factorization
- subspace methods
- high dimensional data
- linear discriminant analysis
- subspace projection
- linear projection
- high dimensional
- face images
- data sets
- neural classifier
- failure modes
- image processing
- kernel pca
- input variables
- singular value decomposition
- random projections
- signal processing
- error analysis
- causal relationships
- directed acyclic graph
- subspace analysis
- feature selection
- discriminant analysis