The geometry of invariants for generalized coherence tests

Stephen D. Howard, Douglas Cochran, Songsri Sirianunpiboon

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

1 Scopus citations

Abstract

This paper considers the problem of testing for mutual independence of multiple sets of complex Gaussian vectors. This problem has classical roots in statistics and has been of recent interest in the signal processing literature in connection with multi-channel signal detection. The maximal invariant statistic for this problem is described both as a collection of subspaces of the data space (i.e., points on a complex Grassmannian manifold) and as a corresponding set of complex matrices. The distribution of the maximal invariant is also derived under both hypotheses in the testing problem.

Original languageEnglish (US)
Title of host publication2016 IEEE Information Theory Workshop, ITW 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages340-344
Number of pages5
ISBN (Electronic)9781509010905
DOIs
StatePublished - Oct 21 2016
Event2016 IEEE Information Theory Workshop, ITW 2016 - Cambridge, United Kingdom
Duration: Sep 11 2016Sep 14 2016

Other

Other2016 IEEE Information Theory Workshop, ITW 2016
CountryUnited Kingdom
CityCambridge
Period9/11/169/14/16

Keywords

  • Invariance
  • Maximal invariant
  • Multiple-channel detection
  • Wijsman's Theorem

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Software
  • Signal Processing

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    Howard, S. D., Cochran, D., & Sirianunpiboon, S. (2016). The geometry of invariants for generalized coherence tests. In 2016 IEEE Information Theory Workshop, ITW 2016 (pp. 340-344). [7606852] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITW.2016.7606852