Reduced complexity online sparse signal reconstruction using projections onto weighted ℓ1 balls

Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, S. McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper presents a novel online method for sparse signal reconstruction. In particular, the notion of sub-dimensional projections is introduced, which allows a significant complexity reduction in the Adaptive Projection-based Algorithm using Weighted ℓ 1 balls (APWL1). This is achieved without sacrificing performance. The proposed method is evaluated in both stationary and time-varying environments and its performance is compared with state-of-the-art online and batch LASSO-based methods.
Original languageEnglish
Title of host publication17th International Conference on Digital Signal Processing 2011
PublisherIEEE
ISBN (Electronic)9781457702747
ISBN (Print)9781457702730
DOIs
Publication statusPublished - 2011
Event17th International Conference on Digital Signal Processing 2011 - Corfu, Greece
Duration: 6 Jul 20118 Jul 2011

Conference

Conference17th International Conference on Digital Signal Processing 2011
Abbreviated titleDSP 2011
Country/TerritoryGreece
CityCorfu
Period6/07/118/07/11

Keywords

  • Adaptive filtering
  • Online signal reconstruction
  • projections
  • sparsity

ASJC Scopus subject areas

  • Signal Processing

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