spgl1-1.7

所属分类:行业发展研究
开发工具:matlab
文件大小:65KB
下载次数:56
上传日期:2010-03-21 17:14:49
上 传 者fulon
说明:  spgl1的最新版本1.7,用于图像处理中的大规模稀疏重建。
(spgl1 the latest version 1.7, for image processing of large-scale sparse reconstruction.)

文件列表:
spgl1-1.7\ChangeLog (3861, 2009-05-21)
spgl1-1.7\Contents.m (697, 2009-05-21)
spgl1-1.7\COPYING (26436, 2009-05-21)
spgl1-1.7\spgdemo.m (16195, 2009-05-21)
spgl1-1.7\spgsetup.m (1608, 2009-05-21)
spgl1-1.7\spgSetParms.m (4725, 2009-05-21)
spgl1-1.7\spgl1.m (30253, 2009-05-21)
spgl1-1.7\spg_bp.m (1594, 2009-05-21)
spgl1-1.7\spg_bpdn.m (1814, 2009-05-21)
spgl1-1.7\spg_lasso.m (1626, 2009-05-21)
spgl1-1.7\spg_mmv.m (2853, 2009-05-21)
spgl1-1.7\spg_group.m (2513, 2009-05-21)
spgl1-1.7\NormL1_dual.m (63, 2009-05-21)
spgl1-1.7\NormL1_primal.m (63, 2009-05-21)
spgl1-1.7\NormL1_project.m (227, 2009-05-21)
spgl1-1.7\NormL12_dual.m (221, 2009-05-21)
spgl1-1.7\NormL12_primal.m (209, 2009-05-21)
spgl1-1.7\NormL12_project.m (463, 2009-05-21)
spgl1-1.7\NormGroupL2_dual.m (184, 2009-05-21)
spgl1-1.7\NormGroupL2_primal.m (176, 2009-05-21)
spgl1-1.7\NormGroupL2_project.m (375, 2009-05-21)
spgl1-1.7\private\ensure.m (1561, 2009-05-21)
spgl1-1.7\private\heap.c (6398, 2009-05-21)
spgl1-1.7\private\heap.h (3660, 2009-05-21)
spgl1-1.7\private\lsqr.m (11849, 2009-05-21)
spgl1-1.7\private\oneProjectorCore.c (5704, 2009-05-21)
spgl1-1.7\private\oneProjectorCore.h (1485, 2009-05-21)
spgl1-1.7\private\oneProjector.m (2838, 2009-05-21)
spgl1-1.7\private\oneProjectorMex.c (4423, 2009-05-21)
spgl1-1.7\private\oneProjectorMex.m (3797, 2009-05-21)
spgl1-1.7\private\oneProjectorMex.mexglx (10390, 2009-05-21)
spgl1-1.7\private\oneProjectorMex.mexmaci (17664, 2009-05-21)
spgl1-1.7\private\oneProjectorMex.mexw32 (9216, 2009-05-21)

SPGL1: Spectral Projected Gradient for L1 minimization ------------------------------------------------------ 1. Introduction =============== Thank you for downloading the SPGL1 solver! SPGL1 is a Matlab solver for large-scale one-norm regularized least squares. It is designed to solve any of the following three problems: 1. Basis pursuit denoise (BPDN): minimize ||x||_1 subject to ||Ax - b||_2 <= sigma, 2. Basis pursuit (BP): minimize ||x||_1 subject to Ax = b 3. Lasso: minimize ||Ax - b||_2 subject to ||x||_1 <= tau, The matrix A can be defined explicily, or as an operator (i.e., a function) that return both both Ax and A'y. SPGL1 can solve these three problems in both the real and complex domains. 2. Quick start ============== Start Matlab and make sure the working directory is set to the directory containing the SPGL1 source files. When this is done, run >> spgdemo at the Matlab prompt. This script illustrates various uses of SPGL1: - Solve (BPDN) for some sigma > 0 - Solve (Lasso) - Solve (BP) - Solve a (BP) problem in complex variables - Sample the entire Pareto frontier (i.e., ||Ax-b||_2 vs ||x||_1) for a small test problem. 3. Installation =============== 3.1 MEX interface ------------------ A vital component of SPGL1 is a routine (oneProjector.m) for projecting vectors onto the one-norm ball. The default distribution includes a pure Matlab version of oneProjector which should work on all platforms, and also a C-version of this routine that is more efficient on large problems. Precompiled MEX interfaces to the C implementation of oneProjector are included for Windows (oneProjector.dll), Linux/x86 (oneProjector.mexglx) and MacOSX/Intel (oneProjector.mexmaci). If you need to compile the MEX interface on your own machine, run the following command at the Matlab prompt: >> spgsetup or, equivalently, change to the "private" directory and issue the command >> mex oneProjector.c oneProjector_core.c -output oneProjector -DNDEBUG If the MEX interface cannot be found, SPGL1 falls back to the slower Matlab implementation of oneProjector. 3.2 Path --------- In order to use SPGL1 from any directory other than the one containing the main spgl1 routine, add the SPGL1 package to your default path: >> addpath where is the location of spgl1.m. You can also add this command to your startup.m file. 4. References ============= The algorithm implemented by SPGL1 is described in the paper E. van den Berg and M. P. Friedlander, "Probing the Pareto frontier for basis pursuit solutions", UBC Computer Science Technical Report TR-2008-01, January 2008. Available at http://www.optimization-online.org/DB_FILE/2008/01/1889.pdf $Id: README 769 2008-01-29 23:19:36Z mpf $

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