Toolbox Sparse Optmization

Optimization codes for sparsity related signal processing
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Actualizado 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.

Citar como

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

Compatibilidad con la versión de MATLAB
Se creó con R2007a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Agradecimientos

Inspiración para: CoSaMP and OMP for sparse recovery

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Versión Publicado Notas de la versión
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