Solution of a Bivariate l(1) Regularized Problem


Bayram I.

IEEE SIGNAL PROCESSING LETTERS, vol.23, no.5, pp.653-657, 2016 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 5
  • Publication Date: 2016
  • Doi Number: 10.1109/lsp.2016.2544949
  • Title of Journal : IEEE SIGNAL PROCESSING LETTERS
  • Page Numbers: pp.653-657

Abstract

We derive the mapping that takes an observation vector to the minimizer of a bivariate cost consisting of the sum of a quadratic data fidelity term and an l(1) norm. The derived mapping is useful for accelerating convergence of iterative algorithms that aim to solve l(1) regularized problems. We discuss how to use the mapping in practice and demonstrate the improvement in convergence rate with numerical experiments.