Oblique pursuits for compressed sensing with random anisotropic measurements

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

Abstract

Compressed sensing enables universal, simple, and reduced-cost acquisition by exploiting a sparse signal model. Most notably, recovery of the signal by computationally efficient algorithms is guaranteed for certain random measurement models, which satisfy the so-called isotropy property. However, in real-world applications, this property is often not satisfied. We propose two related changes in the existing framework for the anisotropic case: (i) a generalized RIP called the restricted biorthogonality property (RBOP); and (ii) correspondingly modified versions of existing greedy pursuit algorithms, which we call oblique pursuits. Oblique pursuits provide recovery guarantees via the RBOP without requiring the isotropy property; hence, these recovery guarantees apply to practical acquisition schemes. Numerical results show that oblique pursuits also perform better than their conventional counterparts.

Original languageEnglish (US)
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages849-853
Number of pages5
DOIs
StatePublished - Dec 19 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: Jul 7 2013Jul 12 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2013 IEEE International Symposium on Information Theory, ISIT 2013
CountryTurkey
CityIstanbul
Period7/7/137/12/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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  • Cite this

    Lee, K., Bresler, Y., & Junge, M. (2013). Oblique pursuits for compressed sensing with random anisotropic measurements. In 2013 IEEE International Symposium on Information Theory, ISIT 2013 (pp. 849-853). [6620346] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2013.6620346