Passive and Active Sampling for Piecewise-Smooth Graph Signals

Rohan Varma, Jelena Kovačević

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

Abstract

In this work, we study the sampling of piecewise smooth- graph signals that exhibit an inhomogeneous level of smoothness over the graph and are characterized by have abrupt, localized discontinuities between smooth regions of the graph. We propose an extension to the graph trend filtering framework under the sampling setting and present an ADMM-algorithm to efficiently reconstruct piecewise-smooth graph signals. Further, to alleviate the limitations of passive sampling in this setting, we develop an active sampling strategy that incorporates feedback to focus the sampling procedure near the boundary or discontinuities. We then conduct experiments that exhibit the performance of our algorithm on large complex graphs and validate the efficacy of our sampling strategies.

Original languageEnglish (US)
Title of host publication2019 13th International Conference on Sampling Theory and Applications, SampTA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728137414
DOIs
StatePublished - Jul 2019
Event13th International Conference on Sampling Theory and Applications, SampTA 2019 - Bordeaux, France
Duration: Jul 8 2019Jul 12 2019

Publication series

Name2019 13th International Conference on Sampling Theory and Applications, SampTA 2019

Conference

Conference13th International Conference on Sampling Theory and Applications, SampTA 2019
Country/TerritoryFrance
CityBordeaux
Period7/8/197/12/19

Keywords

  • graph signal processing
  • graph trend filtering
  • piecewise smooth
  • sampling

ASJC Scopus subject areas

  • Statistics and Probability
  • Signal Processing
  • Analysis
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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