Sufficient conditions on stable recovery of sparse signals with partial support information

Xiaohan Yu, Seung Jun Baek

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

In this letter, we study signal reconstruction from compressed sensing measurements. We propose new sufficient conditions for stable recovery when partial support information is available. Weighted ℓ1- minimization is adopted to recover the original signal under three noise models. The proposed approach is to use Ozeki's inequality and shifting inequality in order to bound the errors in the associated weighted ℓ1 -minimization. Our result offers generalized performance bounds on recovery capturing known support information. Improved sufficient conditions for recovery are derived based on our results, even for the cases where the accuracy of prior support information is arbitrarily low.

Original languageEnglish
Article number6488730
Pages (from-to)539-542
Number of pages4
JournalIEEE Signal Processing Letters
Volume20
Issue number5
DOIs
Publication statusPublished - 2013 Apr 17

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Keywords

  • Compressive sensing (CS)
  • partial support information
  • weighted ℓ-minimization

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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