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Toolbox Sparse Optmization

version (805 KB) by Gabriel Peyre
Optimization codes for sparsity related signal processing


Updated 03 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.

Cite As

Gabriel Peyre (2021). Toolbox Sparse Optmization (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (23)

Imam Santoso

prabha A

Hi,I need coding for compressing sensing based cooperative communication with decode and forward relay networks .

Han Huang

some files are lost

Han Huang

Minkyung Kim

Hi, Gabriel. I am really appreciate for your nice code !
I have a question, how i can apply some constraint ? (like, X >= 0)

maedeh kafiyan

it's better if you publish your references

Pantelis Sopasakis


Erick Zhou

Erick Zhou

Hi, Gabriel. Have you published papers related to this toolbox? Would you please give me some ideas about how to choose the lambda in your toolbox. thank you.

Abdur Rehman

mimi sam


very good


Thanks very much


some files are lost such as Homotopie2.m
you'd better update your file.


it will be better if your zip contains a file of description

Ganesh AS

Is there any GUI associated with this?

Farshid Zoghalchi

Andrea Santos

Hi, Gabriel your work is really interesting.

Actually, I am working with unmixing techniques for images and I want to apply sparse positive matrix factorization. I find your code could be very useful to me but, I do not have clear how to use the code. Can you help me sending me maybe a readme file with more details. I am really excited to use these functions.

dafav ffaffb

There are some file lost in you code.Please give a whole code.

Prasad Gurlahosur

Jianwei Ma

Hello Gabriel, Thanks very much for your code. But it will be better to provide a readme file with more detailed description.

li hengjian

Gabriel Peyré ,you very good !
just one year!,you havedone a lot of work on
signal processing

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

Inspired: CoSaMP and OMP for sparse recovery

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