Solution of a Bivariate l(1) Regularized Problem

Bayram I.

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

  • Publication Type: Article / Article
  • Volume: 23 Issue: 5
  • Publication Date: 2016
  • Doi Number: 10.1109/lsp.2016.2544949
  • Journal Name: IEEE SIGNAL PROCESSING LETTERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.653-657
  • Istanbul Technical University Affiliated: No

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.