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2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
The classical compressed sensing problem is to find the sparsest solution to an underdetermined system of linear equations. A good convex approximation to this problem is to minimize the 1 norm subject to affine constraints. The Iterative Reweighted Least Squares (IRLSp) algorithm (0 < p ≤ 1), has been proposed as a method to solve the p (p ≤ 1) minimization problem with affine constraints. Recently Chartrand et al observed that IRLSp with p < 1 has better empirical performance than 1doi:10.1109/allerton.2010.5706969 fatcat:zqqw4gbesndobge3maqrtxsvuy