KPCAREC |
Reconstructs image after kernel PCA.
Synopsis:
Y = kpcarec(X,model)
Description:
Input data X are projected using kernel projection trained
the by Kernel PCA [Mika99b]. The RBF kernel is assumed. This
function computes the preimages Y from the input space
corresponding to the projected data are.
X -> projection to -> preimage -> Y
kernel space problem
by Kernel PCA
Input:
X [dim x num_data] Input vectors.
model [struct] Kernel projection with RBF kernel;
see 'help kernelproj'.
Output:
Y [dim x num_data] Output data.
See also
KPCA, PCAREC.
About: Statistical Pattern Recognition Toolbox
(C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac
Czech Technical University Prague
Faculty of Electrical Engineering
Center for Machine Perception
Modifications:
17-may-2004, VF
22-apr-2004, VF
17-mar-2004, VF, created.