Reduced complexity online sparse signal reconstruction using projections onto weighted 1 balls

Yannis Kopsinis, Konstantinos Slavakis, Sergios Theodoridis, Steve McLaughlin

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

4 Scopus citations

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 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 (US)
Title of host publication17th DSP 2011 International Conference on Digital Signal Processing, Proceedings
DOIs
StatePublished - Sep 29 2011
Event17th International Conference on Digital Signal Processing, DSP 2011 - Corfu, Greece
Duration: Jul 6 2011Jul 8 2011

Publication series

Name17th DSP 2011 International Conference on Digital Signal Processing, Proceedings

Other

Other17th International Conference on Digital Signal Processing, DSP 2011
CountryGreece
CityCorfu
Period7/6/117/8/11

Keywords

  • Adaptive filtering
  • Online signal reconstruction
  • projections
  • sparsity

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