Enhancing Sparsity by Reweighted ℓ1 Minimization

@article{Cands2007EnhancingSB,
  title={Enhancing Sparsity by Reweighted ℓ1 Minimization},
  author={E. Cand{\`e}s and M. Wakin and Stephen P. Boyd},
  journal={Journal of Fourier Analysis and Applications},
  year={2007},
  volume={14},
  pages={877-905}
}
  • E. Candès, M. Wakin, Stephen P. Boyd
  • Published 2007
  • Mathematics
  • Journal of Fourier Analysis and Applications
  • It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by constrained ℓ1 minimization. In this paper, we study a novel method for sparse signal recovery that in many situations outperforms ℓ1 minimization in the sense that substantially fewer measurements are needed for exact recovery. The algorithm consists of solving a sequence of weighted ℓ1-minimization… CONTINUE READING
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