NDLI: Time-varying higher-order cumulant spectra: application to the analysis of composite FM signals in multiplicative and additive noise

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Time-varying higher-order cumulant spectra: application to the analysis of composite FM signals in multiplicative and additive noise

Periodic uncertainty in periodic spectral analysis of processes associated with periodic phenomena

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A reduced complexity ESPRIT method and its generalization to an antenna of partially unknown shape

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Rank determination in time-series analysis

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Time-varying higher-order cumulant spectra: application to the analysis of composite FM signals in multiplicative and additive noise

Content Provider	IEEE Xplore Digital Library
Author	Boashash, B. Ristic, B.
Copyright Year	1994
Description	Author affiliation: Signal Process. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia (Boashash, B.; Ristic, B.)
Abstract	Time-varying higher-order spectra (TV-HOS), have recently been proposed for (poly)spectral analysis of non-stationary signals. Two new results are presented here. First, the cumulant TV-HOS (in particular, cumulant Wigner-Ville trispectrum (WVT)), is shown to preserve the essential properties of cumulant higher-order spectra (e.g. eliminate Gaussian additive noise) and at the same time characterise time-variations of the signal's frequency content. Second, when dealing with composite FM signals, a special kind of "non-oscillating cross-terms" is shown to appear in the moment TV-HOS time-frequency subspace. We show that these cross-terms cannot be eliminated by smoothing the WVT, but rather by an appropriate projection from the full time-multi-frequency space to a time-frequency subspace.<>
File Size	288152
File Format	PDF
ISBN	0780317750
ISSN	15206149
DOI	10.1109/ICASSP.1994.389812
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-04-19
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal analysis Polynomials Time frequency analysis Additive noise Signal processing Australia Smoothing methods Performance analysis Higher order statistics Gaussian noise
Content Type	Text
Resource Type	Article

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