Kernel principal component analysis for UWB-based ranging.
Vladimir SavicErik G. LarssonJavier Ferrer-CollPeter F. StenumgaardPublished in: SPAWC (2014)
Keyphrases
- kernel principal component analysis
- ultra wide band
- discriminant analysis
- kernel pca
- feature extraction
- kernel function
- principal components
- preprocessing
- principal component analysis
- feature space
- ultra wideband
- kernel methods
- face recognition
- high dimensional
- kernel matrix
- kernel fisher discriminant analysis
- small number of training samples
- linear discriminant analysis
- classification method
- support vector machine svm
- feature vectors
- gabor wavelets
- subspace methods
- high dimensional feature space
- data sets
- dimensionality reduction
- feature selection
- machine learning