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This very simple example of L1 minimization is reproduced for implementation on matlab. The original example was posted on Rip's Applied
Mathematics Blog on March 28, 2011 entitled "Compressed Sensing: the L1
norm finds sparse solutions".
One needs to download the L1-MAGIC package in order to perform the l1 minimization on matlab.
This example was very good for illustrating how L1 minimization can identify a sparse vector. Here x is the sparse vector. A is the kxN incoherent matrix and B are the coefficients. The example shows how we can find the original x. xp should be approximately equal to x.
Cite As
Marcos Bolanos (2026). Compressive Sensing Simple Example (https://se.mathworks.com/matlabcentral/fileexchange/33813-compressive-sensing-simple-example), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (1.5 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
