Description: KPCA procedure uses the kernel nonlinear data mapped into linear space, and then using principal component analysis to extract feature data.
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File list (Check if you may need any files):
1kernel-ica1_1
..............\kernel-ica1_1
..............\.............\amari_distance.m
..............\.............\chol_gauss.c
..............\.............\chol_gauss.m
..............\.............\chol_hermite.c
..............\.............\chol_hermite.m
..............\.............\chol_poly.c
..............\.............\chol_poly.m
..............\.............\contrast_emp_grad.m
..............\.............\contrast_emp_grad_oneunit.m
..............\.............\contrast_ica.m
..............\.............\contrast_ica_oneunit.m
..............\.............\contrast_update_oneunit.m
..............\.............\demo_kernel_ica.m
..............\.............\empder_search.m
..............\.............\empder_search_oneunit.m
..............\.............\global_mini.m
..............\.............\global_mini_oneunit.m
..............\.............\global_mini_sequential.m
..............\.............\kernel_ica.m
..............\.............\rand_orth.m
..............\.............\readme.txt
..............\.............\update_contrast.m
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