based classification (SRC) has been widely used for facerecognition (FR). SRC first codes a testing sample as asparse linear combination of all the training samples, andthen classifies the testing sample by evaluating which classleads to the minimum representation error. While theimportance of sparsity is much emphasized in SRC andmany related works, the use of collaborative representation(CR) in SRC is ignored by most literature.




File list:
spgl1-1.8
........\private
........\.......\ensure.m
........\.......\heap.c
........\.......\heap.h
........\.......\lsqr.m
........\.......\oneProjector.m
........\.......\oneProjectorCore.c
........\.......\oneProjectorCore.h
........\.......\oneProjectorMex.c
........\.......\oneProjectorMex.m
........\.......\oneProjectorMex.mexglx
........\.......\oneProjectorMex.mexmaci
........\.......\oneProjectorMex.mexw32
........\ChangeLog
........\Contents.m
........\COPYING
........\NormGroupL2_dual.m
........\NormGroupL2_primal.m
........\NormGroupL2_project.m
........\NormL12_dual.m
........\NormL12_primal.m
........\NormL12_project.m
........\NormL1NN_dual.m
........\NormL1NN_primal.m
........\NormL1NN_project.m
........\NormL1_dual.m
........\NormL1_primal.m
........\NormL1_project.m
........\README
........\spgdemo.m
........\spgl1.m
........\spgSetParms.m
........\spgsetup.m
........\spg_bp.m
........\spg_bpdn.m
........\spg_group.m
........\spg_lasso.m
........\spg_mmv.m