The Geometry of Coherence and Its Application to Cyclostationary Time Series

Stephen D. Howard, Songsri Sirianunpiboon, Douglas Cochran

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

Abstract

The consequences of cyclostationary structure in a random process have traditionally been described in terms of the correlation or coherence of pairs of particular time and frequency shifted versions of the process. However, cyclostationarity, and more generally almost cyclostationarity, are manifest in the mutual coherence of subspaces spanned by sets of time and frequency shifted versions of the process. The generalized coherence framework allows any finite collection of pertinent samples of the cyclic autocorrelation function estimates formed from the measured signal data to be combined into a detection statistic. This paper develops the subspace coherence theory of almost cyclostationary processes as a guide to constructing such detectors in both the time and spectral domains.

Original languageEnglish (US)
Title of host publication2018 IEEE Statistical Signal Processing Workshop, SSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages766-770
Number of pages5
ISBN (Print)9781538615706
DOIs
StatePublished - Aug 29 2018
Event20th IEEE Statistical Signal Processing Workshop, SSP 2018 - Freiburg im Breisgau, Germany
Duration: Jun 10 2018Jun 13 2018

Other

Other20th IEEE Statistical Signal Processing Workshop, SSP 2018
CountryGermany
CityFreiburg im Breisgau
Period6/10/186/13/18

Fingerprint

Time series
Geometry
geometry
random processes
Random processes
Autocorrelation
autocorrelation
Statistics
statistics
Detectors
detectors
estimates

Keywords

  • Coherence
  • Cyclostationarity
  • Multiple-channel detection

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation
  • Computer Networks and Communications

Cite this

Howard, S. D., Sirianunpiboon, S., & Cochran, D. (2018). The Geometry of Coherence and Its Application to Cyclostationary Time Series. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018 (pp. 766-770). [8450812] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSP.2018.8450812

The Geometry of Coherence and Its Application to Cyclostationary Time Series. / Howard, Stephen D.; Sirianunpiboon, Songsri; Cochran, Douglas.

2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 766-770 8450812.

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

Howard, SD, Sirianunpiboon, S & Cochran, D 2018, The Geometry of Coherence and Its Application to Cyclostationary Time Series. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450812, Institute of Electrical and Electronics Engineers Inc., pp. 766-770, 20th IEEE Statistical Signal Processing Workshop, SSP 2018, Freiburg im Breisgau, Germany, 6/10/18. https://doi.org/10.1109/SSP.2018.8450812
Howard SD, Sirianunpiboon S, Cochran D. The Geometry of Coherence and Its Application to Cyclostationary Time Series. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 766-770. 8450812 https://doi.org/10.1109/SSP.2018.8450812
Howard, Stephen D. ; Sirianunpiboon, Songsri ; Cochran, Douglas. / The Geometry of Coherence and Its Application to Cyclostationary Time Series. 2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 766-770
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