## Subspace methods

## Robust estimation of subspace coefficients

This package contains Matlab functions, which perform robust estimation of subspace coefficients in PCA, CCA and LDA methods. It contains the following files (Matlab functions):

- PCA Principal Component Analysis. Creates the principal subspace.
- IS2FS Maps images from image space to feature space.
- FS2IS Maps vectors of subspace coefficients from feature space to image space.
- IS2FSROB Maps vectors of subspace coefficients from feature space to image space in a robust manner.
- CCA Canonical Correlation Analysis. Computes canonical correlation vectors.
- CCAAPCA CCA-after-PCA. Calculates CCA of augmented PCA coefficient vectors.
- LDA Linear Discriminant Analysis. Computes LDA eigenvectors.
- LDAAPCA LDA-after-PCA. Calculates LDA of augmented PCA coefficient vectors.
- DISPIMGS Displays images.
- DEMOPCA Demo of robust estimation of principal components.
- DEMOCCA Demo of robust estimation of canonical correlation coefficients.