Performance analysis of stochastic signal detection with compressive measurements

Thakshila Wimalajeewa, Hao Chen, Pramod K. Varshney

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

17 Scopus citations

Abstract

Compressed sensing (CS) enables the recovery of sparse or compressible signals from relatively a small number of randomized measurements compared to Nyquist-rate samples. Although most of the CS literature has focused on sparse signal recovery, exact recovery is not actually necessary in many signal processing applications. Solving inference problems with compressive measurements has been addressed by recent CS literature. This paper takes some further steps to investigate the potential of CS in signal detection problems. We provide theoretical performance limits verified by simulations for detection performance in arbitrary random signal detection with compressive measurements.

Original languageEnglish (US)
Title of host publicationConference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
Pages813-817
Number of pages5
DOIs
StatePublished - Dec 1 2010
Event44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010 - Pacific Grove, CA, United States
Duration: Nov 7 2010Nov 10 2010

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
CountryUnited States
CityPacific Grove, CA
Period11/7/1011/10/10

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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    Wimalajeewa, T., Chen, H., & Varshney, P. K. (2010). Performance analysis of stochastic signal detection with compressive measurements. In Conference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010 (pp. 813-817). [5757678] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2010.5757678