Comparison of orthogonal matching pursuit implementations

We study the numerical and computational performance of three implementations of orthogonal matching pursuit: one using the QR matrix decomposition, one using the Cholesky matrix decomposition, and one using the matrix inversion lemma. We find that none of these implementations suffer from numerical error accumulation in the inner products or the solution. Furthermore, we empirically compare the computational times of each algorithm over the phase plane.