文件名称:spgl1-1.8
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based classification (SRC) has been widely used for face
recognition (FR). SRC first codes a testing sample as a
sparse linear combination of all the training samples, and
then classifies the testing sample by evaluating which class
leads to the minimum representation error. While the
importance of sparsity is much emphasized in SRC and
many related works, the use of collaborative representation
(CR) in SRC is ignored by most literature.
recognition (FR). SRC first codes a testing sample as a
sparse linear combination of all the training samples, and
then classifies the testing sample by evaluating which class
leads to the minimum representation error. While the
importance of sparsity is much emphasized in SRC and
many related works, the use of collaborative representation
(CR) in SRC is ignored by most literature.
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spgl1-1.8
.........\COPYING
.........\ChangeLog
.........\Contents.m
.........\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
.........\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
.........\spgSetParms.m
.........\spg_bp.m
.........\spg_bpdn.m
.........\spg_group.m
.........\spg_lasso.m
.........\spg_mmv.m
.........\spgdemo.m
.........\spgl1.m
.........\spgsetup.m