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In compressive sensing, generalized Orthogonal Matching Pursuit (gOMP) algorithm generalizes OMP algorithm by selecting N(N≥1) atoms in each iteration. In this paper, we propose restricted isometry constant based sufficient conditions for gOMP algorithm to correctly recover the support of significant components of signal when both measurement dictionary and measurement signal are contaminated with...
The generalized Orthogonal Matching Pursuit (gOMP) algorithm generalizes the OMP algorithm by selecting more than one atom in each iteration. Under conventional settings, the gOMP algorithm iterates K loops where K is the sparsity of the sparse signal that is to be recovered. Thus, K is usually unknown beforehand. We propose stopping rules along with sufficient conditions for the gOMP algorithm to...
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