Toolbox Sparse Optmization

Optimization codes for sparsity related signal processing
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Mise à jour 3 jan. 2011

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This toolbox contains the implementation of what I consider to be fundamental algorithms
for non-smooth convex optimization of structured functions. These algorithms might not be the fasted
(although they certainly are quite efficient), but they all have a simple implementation in term
of black boxes (gradient and proximal mappings, given as callbacks). However, you should have
some knowledge about what is a gradient operator and a proximal mapping in order to be able
to use this toolbox on your own problems. I suggest you have a look at the
"suggested readings" for some more information about all this.

Citation pour cette source

Gabriel Peyre (2024). Toolbox Sparse Optmization (https://www.mathworks.com/matlabcentral/fileexchange/16204-toolbox-sparse-optmization), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2007a
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Remerciements

A inspiré : CoSaMP and OMP for sparse recovery

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Version Publié le Notes de version
1.5.0.0

Totally changed the toolbox to contain only optimization codes.

1.3.0.0

Modified license.
Remove GPL files. Gabriel said he will redo this in January.

1.2.0.0

Update of Licence

1.1.0.0

BSD Licence