Toolbox Sparse Optmization
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
Platform Compatibility
Windows macOS LinuxCategories
- Signal Processing > Signal Processing Toolbox > Transforms, Correlation, and Modeling > Correlation and Convolution >
Tags
Acknowledgements
Inspired: CoSaMP and OMP for sparse recovery
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.