Exact Bayesian test for a common rank-one component in white noise

Songsri Sirianunpiboon, Stephen D. Howard, Douglas Cochran

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

1 Scopus citations

Abstract

Unknown and arbitrary rank-one signals are collected by two arrays of sensors. This paper constructs an exact invariant Bayesian detector for deciding if the two sets of data are generated by the same rank-one signal. This detector is compared to the generalized likelihood ratio test (GLRT) and shown in simulation to give significantly better performance.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages1496-1499
Number of pages4
Volume2016-February
ISBN (Print)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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  • Cite this

    Sirianunpiboon, S., Howard, S. D., & Cochran, D. (2016). Exact Bayesian test for a common rank-one component in white noise. In Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2016-February, pp. 1496-1499). [7421394] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421394