25 April 1995 Trends in spectral analysis: higher order and cyclic statistics
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Georgios B. Giannakis "Trends in spectral analysis: higher order and cyclic statistics", Proc. SPIE 10279, Digital Signal Processing Technology: A Critical Review, 1027906 (25 April 1995); doi: 10.1117/12.204211; https://doi.org/10.1117/12.204211
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