CoSaMP and OMP for sparse recovery

버전 1.7 (10.7 KB) 작성자: Stephen Becker
Orthogonal Matching Pursuit (OMP) and Compressive Sampling Matched Pursuit (CoSaMP).
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업데이트 날짜: 2016/8/5

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Orthogonal matching Pursuit (OMP) and Compressive Sampling Matched Pursuit (CoSaMP) algorithm (see Needell and Tropp's 2008 paper ). This implementation allows several variants, and it also allows you to specify a matrix via function handles (useful if your matrix represents an FFT or similar).
A demo code shows how to use both the OMP.m and CoSaMP.m functions.
OMP and CoSaMP are useful for sparse recovery problems; in particular, they can be used for compressed sensing (aka compressive sampling), image denoising and deblurring, seismic tomography problems, MRI, etc.

Another good OMP implementation (C++, Matlab) is here:
(Updated, March 2012: SPAMS now has python and R bindings as well)

And a CoSaMP implementation (I haven't tested):
Edit: that CoSaMP implementation mentioned above is buggy. Read this:

Update, Feb 2012: for a blog discussion of several way to implement CoSaMP, see this website:

인용 양식

Stephen Becker (2024). CoSaMP and OMP for sparse recovery (, MATLAB Central File Exchange. 검색됨 .

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Fixed bug with complex numbers (Aug 2016)

Fixing the bug for complex mode. Minor changes to the solvers. Added complex data test mode to the test script.

Fixing a bug that affected versions of Matlab prior to 2009b. See

editing description text a bit

Adding new links in the description, and updated the demo file slightly.