Many natural signals have concise representations when expressed in a convenient basis. Consider, for example, the image in Figure 1(a) and its wavelet transform in (b). Although nearly all the image pixels have nonzero values, the wavelet coefficients offer a concise summary: most coefficients are small, and the relatively few large coefficients capture most of the information.

modelcs_v1.1\1D trees\.DS_Store
............\........\cssa1.m
............\........\greedy1.m
............\........\treemp.m
............\........\treemp_example.m
............\........\treemp_fun.m
............\2D trees\.DS_Store
............\........\cosamp_2D_nf.m
............\........\cssa2.m
............\........\greedy2.m
............\........\peppers.png
............\........\treemp_2D_example.m
............\........\treemp_greedy_2D.m
............\........\treemp_nf_2D.m
............\Block sparsity\.DS_Store
............\..............\jsmp.m
............\..............\jsmp_example.m
............\..............\jsmp_fun.m
............\Clustered sparsity\.DS_Store
............\..................\kc.m
............\..................\kc_example.m
............\Delta\.DS_Store
............\.....\bestdelta.m
............\.....\deltarec.m
............\.....\delta_example.m
............\README.txt
............\Sparsity\.DS_Store
............\........\;.m
............\........\cosamp.m
............\........\cosamp_example.m
............\........\cosamp_fun.m
............\........\cosanalysis.m
............\........\cosanalysis.m~
............\........\cosanalysis_example.m
............\........\cosanalysis_example.m~
............\Utils\At_f.m
............\.....\axisfortex.m
............\.....\A_f.m
............\.....\A_I.m
............\.....\A_I_transpose.m
............\.....\bestKCsparse_l1mex.cpp
............\.....\bestKCsparse_l1mex.mexa64
............\.....\bestKCsparse_l1mex.mexglx
............\.....\bestKCsparse_l1mex.mexmaci
............\.....\bestKCsparse_l2mex.cpp
............\.....\bestKCsparse_l2mex.mexa64
............\.....\bestKCsparse_l2mex.mexglx
............\.....\bestKCsparse_l2mex.mexmaci
............\.....\cgsolve.m
............\.....\condense.m
............\.....\genPWpoly.m
............\.....\maskp.m
............\.....\Qdel.m
............\.....\Qfind.m
............\.....\Qins.m
............\.....\Qswap.m
............\.....\rmaxis.m
............\.....\Tfind.m
............\.....\umask.m
............\.....\walk1.m
............\.....\walk2.m
............\1D trees
............\2D trees
............\Block sparsity
............\Clustered sparsity
............\Delta
............\Sparsity
............\Utils
modelcs_v1.1

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