Spectrum-blind signal recovery on graphs

Rohan Varma, Siheng Chen, Jelena Kovačević

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

Abstract

We consider the problem of recovering a graph signal, sparse in the graph spectral domain from a few number of samples. In contrast to most previous work on the sampling of graph signals, the setting is spectrum-blind where we are unaware of the graph d support of the signal. We propose a class of spectrum-blind graph signals and study two recovery strategies based on random and experimentally designed sampling inspired by the compressed sensing paradigm. We further show sampling bounds for graphs, including Erdos-Rényi random graphs. We show that experimentally designed sampling significantly outperforms random sampling for some irregular graph families.

Original languageEnglish (US)
Title of host publication2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-84
Number of pages4
ISBN (Electronic)9781479919635
DOIs
StatePublished - 2015
Event6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 - Cancun, Mexico
Duration: Dec 13 2015Dec 16 2015

Publication series

Name2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015

Other

Other6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
CountryMexico
CityCancun
Period12/13/1512/16/15

Keywords

  • compressed sensing
  • discrete signal processing on graphs
  • sampling
  • signal recovery

ASJC Scopus subject areas

  • Signal Processing
  • Computational Mathematics

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  • Cite this

    Varma, R., Chen, S., & Kovačević, J. (2015). Spectrum-blind signal recovery on graphs. In 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 (pp. 81-84). [7383741] (2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMSAP.2015.7383741