Orthogonal Matching Pursuit Algorithm (OMP)
Orthogonal Matching Pursuit Algorithm (OMP) is a greedy compressed sensing recovery algorithm which selects the best fitting column of the sensing matrix in each iteration. A least squares (LS) optimization is then performed in the subspace spanned by all previously picked columns. This method is less accurate than the Basis pursuit algorithms but has a lower computational complexity. The Matlab function has three inputs: Sparsity K, measurements vector y and sensing matrix A. The output of this function is the recovered sparse vector x.
Cite As
Mohamed Shaban (2024). Orthogonal Matching Pursuit Algorithm (OMP) (https://www.mathworks.com/matlabcentral/fileexchange/50584-orthogonal-matching-pursuit-algorithm-omp), MATLAB Central File Exchange. Retrieved .
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