Signal and Noise Statistics Oblivious Sparse Reconstruction using OMP/OLS

27 Jul 2017Sreejith KallummilSheetal Kalyani

Orthogonal matching pursuit (OMP) and orthogonal least squares (OLS) are widely used for sparse signal reconstruction in under-determined linear regression problems. The performance of these compressed sensing (CS) algorithms depends crucially on the \textit{a priori} knowledge of either the sparsity of the signal ($k_0$) or noise variance ($\sigma^2$)... (read more)

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