Efficient ℓq Minimization Algorithms for Compressive Sensing Based on Proximity Operator

Abstract

This paper considers solving the unconstrained lq-norm (0 ≤ q < 1) regularized least squares (lq-LS) problem for recovering sparse signals in compressive sensing. We propose two highly efficient first-order algorithms via incorporating the proximity operator for nonconvex lq-norm functions into the fast iterative shrinkage/thresholding (FISTA) and the… (More)

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