On a generalization of the iterative soft-thresholding algorithm for the case of non-separable penalty

Inverse Problems, Volume 27, Issue 12, 2011, Pages 125007

Cited by: 26|Views5

Abstract:

An explicit algorithm for the minimization of an $\ell_1$ penalized least squares functional, with non-separable $\ell_1$ term, is proposed. Each step in the iterative algorithm requires four matrix vector multiplications and a single simple projection on a convex set (or equivalently thresholding). Convergence is proven and a 1/N conve...More

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