Iterative Re-weighted Least Squares Algorithms for Non-negative Sparse and Group-sparse Recovery

Algorithms for non-negative sparse recovery are either based on modifications of orthogonal matching pursuit or are based on thresholding of non-negative least squares. Both are variants of techniques proposed for sparse recovery. This work is based on the iterative re-weighted least squares (IRLS) approach for sparse recovery. IRLS has been found to be a simple yet versatile approach that can handle both l 1 -norm and l p -quasi norm (0