Random Sampling for Bandlimited Signals on Product Graphs

Rohan Varma, Jelena Kovačević

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

Abstract

In this work, we construct a structured framework for the efficient random sampling and recovery of bandlimited graph signals that lie on product graphs. Product graphs are a model to construct large complex graphs from smaller simpler building blocks we call graph atoms, and are a convenient tool to model rich classes of multi-modal graph-structured data. Our randomized sampling framework prescribes an optimal sampling distribution over the nodes of the product graph constructed by only processing these smaller graph atoms. As a result, the framework achieves significant savings in computational complexity with respect to previous works that do not exploit the inherent structure of product graphs.

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

  • bandlimited
  • graph signal
  • product graph
  • random
  • sampling

ASJC Scopus subject areas

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

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