An efficient spectral-Galerkin approximation based on dimension reduction scheme for transmission eigenvalues in polar geometries.
Shixian RenTing TanJing AnPublished in: Comput. Math. Appl. (2020)
Keyphrases
- dimension reduction
- principal component analysis
- singular value decomposition
- laplacian matrix
- low dimensional
- high dimensional
- feature extraction
- manifold learning
- high dimensional problems
- data mining and machine learning
- linear discriminant analysis
- high dimensional data
- cluster analysis
- random projections
- dimensionality reduction
- discriminative information
- variable selection
- feature space
- partial least squares
- machine learning
- covariance matrix
- feature selection
- partial differential equations
- differential equations
- image processing
- data sets
- high dimensionality
- principal components
- input data
- preprocessing
- hash functions
- pattern recognition
- bayesian networks
- clustering algorithm
- manifold embedding