Sparse Approximate Solutions to Linear Systems
The code implements the algorithm presented by B.K.Natarajan in SIAM. April '95.
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The following problem is considered: given a matrix A in R(mxn), a vector b in R(m) and e>0, compute a vector x satisfying norm(Ax-b)<=e if such exists, such that x has the fewest number of non-zero entries over all such vectors.
Cite As
Thanasis (2026). Sparse Approximate Solutions to Linear Systems (https://au.mathworks.com/matlabcentral/fileexchange/29101-sparse-approximate-solutions-to-linear-systems), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (1.81 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
