Toolbox Sparse Optmization

Optimization codes for sparsity related signal processing
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Updated Mon, 03 Jan 2011 04:39:53 +0000

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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.

Cite As

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

MATLAB Release Compatibility
Created with R2007a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired: CoSaMP and OMP for sparse recovery

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Version Published Release Notes
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