Polyspectral analysis of (almost) cyclostationary signals: LPTV system identification and related applications

Georgios B. Giannakis, Amod V. Dandawate

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

19 Scopus citations

Abstract

Polyspectral estimators are proposed for (almost) cyclostationary signals and are shown to be consistent and asymptotically normal. These estimators are used for identification of linear (almost) periodically time-varying systems. Both non-parametric and parametric approaches are described for input-output and output only identification. Statistical analysis of nonstationary signals with missing observations is treated and tests are developed for checking the presence of cycle frequencies. Frequency estimation and detection of coupling are addressed in the cyclic domain without resorting to phase randomization. All methods are proven to be insensitive to stationary noise and use consistent single record estimators.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Circuits, Systems & Computers
PublisherPubl by Maple Press, Inc
Pages377-382
Number of pages6
ISBN (Print)0818624701
StatePublished - Dec 1 1991
Event25th Asilomar Conference on Signals, Systems & Computers Part 1 (of 2) - Pacific Grove, CA, USA
Duration: Nov 4 1991Nov 6 1991

Publication series

NameConference Record - Asilomar Conference on Circuits, Systems & Computers
Volume1
ISSN (Print)0736-5861

Other

Other25th Asilomar Conference on Signals, Systems & Computers Part 1 (of 2)
CityPacific Grove, CA, USA
Period11/4/9111/6/91

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    Giannakis, G. B., & Dandawate, A. V. (1991). Polyspectral analysis of (almost) cyclostationary signals: LPTV system identification and related applications. In Conference Record - Asilomar Conference on Circuits, Systems & Computers (pp. 377-382). (Conference Record - Asilomar Conference on Circuits, Systems & Computers; Vol. 1). Publ by Maple Press, Inc.