Compressed sensing of diffusion fields under heat equation constraint

Mohammad Rostami, Ngai Man Cheung, Tony Q.S. Quek

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

7 Citations (Scopus)

Abstract

Reconstructing a diffusion field from spatiotemporal measurements is an important problem in engineering and physics with applications in temperature flow, pollution dispersion, and disease epidemic dynamics. In such applications, sensor networks are used as spatiotemporal sampling devices and a relatively large number of spatiotemporal measurements may be required for accurate source field reconstruction. Consequently, due to limitations on the number of nodes in the sensor networks as well as hardware limitations of each sensor, situations may arise where the available spatiotemporal sampling density does not allow for recovery of field details. In this paper, the above limitation is resolved by means of using compressed sensing (CS). We propose to exploit the intrinsic property of diffusive fields as side information to improve the reconstruction results of classic CS which we call diffusive compressed sensing (DCS). Experimental results demonstrate the effectiveness and usefulness of the proposed method in substantial data savings while producing estimates of higher accuracy, as compared to classic CS-base estimates.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4271-4274
Number of pages4
DOIs
Publication statusPublished - 2013 Oct 18
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 2013 May 262013 May 31

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period13-05-2613-05-31

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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