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Thresholded smoothed ℓ0 norm for accelerated sparse recovery

  • Han Wang
  • , Qing Guo
  • , Gengxin Zhang
  • , Guangxia Li
  • , Wei Xiang
  • School of Electronics and Information Engineering, Harbin Institute of Technology
  • Nanjing University of Science and Technology
  • University of Southern Queensland

Research output: Contribution to journalArticlepeer-review

Abstract

Smoothed ℓ0 norm (SL0) is a fast and complex domain extendible sparse recovery algorithm which is suitable for many practical real-time applications. In this letter, we propose an improved algorithm termed 'Thresholded Smoothed ℓ0 Norm (T-SL0) ' for accelerating the iterative process of SL0. T-SL0 introduces an iterative efficiency indicator and compares it with a preset threshold in real time to determine whether or not the current iteration should be executed. Through identifying and bypassing low efficient iterations, our approach converges much faster than the original SL0 algorithm. Experimental results are presented to demonstrate that our approach can accelerate SL0 significantly without loss of accuracy.

Original languageEnglish
Article number7069222
Pages (from-to)953-956
Number of pages4
JournalIEEE Communications Letters
Volume19
Issue number6
DOIs
StatePublished - 1 Jun 2015
Externally publishedYes

Keywords

  • Compressive sensing
  • smoothed ℓ0 norm (SL0)
  • sparse recovery

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