Compressive Sensing Simple Example

Version 1.0.0.0 (1.5 KB) by Marcos Bolanos
Matlab example of L1 Minimization for finding a sparse vector.
3.6
(8)
4.7K Downloads
Updated 17 Nov 2011

View License

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 (2024). Compressive Sensing Simple Example (https://www.mathworks.com/matlabcentral/fileexchange/33813-compressive-sensing-simple-example), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on GPU Computing in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version Published Release Notes
1.0.0.0