A frequency domain test for propriety of complex-valued vector time series

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Title: A frequency domain test for propriety of complex-valued vector time series
Author(s): Chandna, S
Walden, AT
Item Type: Journal Article
Abstract: This paper proposes a frequency domain approach to test the hypothesis that a stationary complex-valued vector time series is proper, i.e., for testing whether the vector time series is uncorrelated with its complex conjugate. If the hypothesis is rejected, frequency bands causing the rejection will be identified and might usefully be related to known properties of the physical processes. The test needs the associated spectral matrix which can be estimated by multitaper methods using, say, K tapers. Standard asymptotic distributions for the test statistic are of no use since they would require K →∞ , but, as K increases so does resolution bandwidth which causes spectral blurring. In many analyses K is necessarily kept small, and hence our efforts are directed at practical and accurate methodology for hypothesis testing for small K. Our generalized likelihood ratio statistic combined with exact cumulant matching gives very accurate rejection percentages. We also prove that the statistic on which the test is based is comprised of canonical coherencies arising from our complex-valued vector time series. Frequency specific tests are combined using multiple hypothesis testing to give an overall test. Our methodology is demonstrated on ocean current data collected at different depths in the Labrador Sea. Overall this work extends results on propriety testing for complex-valued vectors to the complex-valued vector time series setting.
Publication Date: 14-Dec-2016
Date of Acceptance: 28-Nov-2016
URI: http://hdl.handle.net/10044/1/42959
DOI: https://dx.doi.org/10.1109/TSP.2016.2639459
ISSN: 1941-0476
Publisher: IEEE
Start Page: 1425
End Page: 1436
Journal / Book Title: IEEE Transactions on Signal Processing
Volume: 65
Issue: 6
Copyright Statement: © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information.
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Generalized likelihood ratio test (GLRT)
improper complex time series
multichannel signal
multiple hypothesis test
spectral analysis
LIKELIHOOD-RATIO CRITERION
FALSE DISCOVERY RATE
COVARIANCE-STRUCTURES
NORMAL-DISTRIBUTIONS
LABRADOR SEA
SIGNALS
STATISTICS
IMPROPRIETY
Networking & Telecommunications
MD Multidisciplinary
Publication Status: Published
Appears in Collections:Mathematics
Statistics
Faculty of Natural Sciences



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