SparseLab is a Matlab software package designed to find sparse solutions to systems of linear equations, particularly underdetermined systems. See the tabs on the left for an introduction to SparseLab, and for download instructions. Please note a new version, SparseLab 2.0 has been released May 26, 2007. It is available for download on this website. SparseLab is a library of Matlab routines for finding sparse solutions to underdetermined systems. It not only aims to provide tools for sparse representation in a cohesive package to the research community, if also allows researchers in this area to publicly release the code accompanying their published papers. The library is available free of charge over the Internet. SparseLab has over 200 matlab files which are documented, indexed and cross-referenced in various ways. SparseLab makes available, in one package, all the code to reproduce all the figures in the included published articles. The interested reader can inspect the source code to see exactly what algorithms were used, and how parameters were set in producing our figures, and can then modify the source to produce variations on our results. SparseLab has been developed, in part, because of exhortations by Jon Claerbout of Stanford that computational scientists should engage in ”really reproducible” research
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Farajzadeh, Nacer; Pan, Gang; Wu, Zhaohui: Facial expression recognition based on meta probability codes (2014)
- Song, Heping; Wang, Guoli: Sparse signal recovery via ECME thresholding pursuits (2012)
- Doostan, Alireza; Owhadi, Houman: A non-adapted sparse approximation of PDEs with stochastic inputs (2011)
- Loris, Ignace: L1Packv2: A Mathematica package for minimizing an $\ell _1$-penalized functional (2008)