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Proceedings Paper

Trends in spectral analysis: higher order and cyclic statistics
Author(s): Georgios B. Giannakis
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Paper Abstract

Signal processing problems dealing with linear non-Gaussian signals, nonlinearities, and nonstationarities, cannot be addressed completely using time-invariant second-order statistical descriptors. Traditional correlation and spectral analysis are currently generalized to higher-order moments, cumulants, and polyspectra. At the same time there is an effort to cope with structured nonstationarities and in particular with cyclostationary processes which are signals exhibiting periodicity in their statistical behavior. A critical overview of higher-order and cyclic spectral analysis is attempted herein with emphasis on statistical signal processing aspects. Major advances and limitations are described along with some directions for future research.

Paper Details

Date Published: 25 April 1995
PDF: 24 pages
Proc. SPIE 10279, Digital Signal Processing Technology: A Critical Review, 1027906 (25 April 1995); doi: 10.1117/12.204211
Show Author Affiliations
Georgios B. Giannakis, Univ. of Virginia (United States)

Published in SPIE Proceedings Vol. 10279:
Digital Signal Processing Technology: A Critical Review
Panos Papamichalis; Robert D. Kerwin, Editor(s)

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