A symmetric linear neural network that learns principal components and their variances.
Ferdinand PeperHideki NodaPublished in: IEEE Trans. Neural Networks (1996)
Keyphrases
- principal components
- neural network
- linear features
- principal component analysis
- dimensionality reduction
- multivariate data
- hyperplane
- pattern recognition
- bp neural network
- kernel space
- artificial neural networks
- back propagation
- neural network model
- principal components analysis
- principal component regression
- spectral data
- machine learning
- kernel principal component analysis
- weight vector
- covariance matrix
- feature selection
- symmetric matrices