  Face recognition is the very significant field in pattern recognition area.
It has multiple applications in military and finance, to name a few. In this
paper, the combination of the sparse PCA with the nearest-neighbor method (and
with the kernel ridge regression method) will be proposed and will be applied
to solve the face recognition problem. Experimental results illustrate that the
accuracy of the combination of the sparse PCA method (using the proximal
gradient method and the FISTA method) and one specific classification system
may be lower than the accuracy of the combination of the PCA method and one
specific classification system but sometimes the combination of the sparse PCA
method (using the proximal gradient method or the FISTA method) and one
specific classification system leads to better accuracy. Moreover, we recognize
that the process computing the sparse PCA algorithm using the FISTA method is
always faster than the process computing the sparse PCA algorithm using the
proximal gradient method.
