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.
|Original language||English (US)|
|Number of pages||24|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Apr 28 1995|
|Event||Digital Signal Processing Technology: A Critical Review 1995 - Orlando, United States|
Duration: Apr 17 1995 → Apr 21 1995
Bibliographical noteFunding Information:
This work was supported by ONR Grant N0014 -93 -1 -0485.
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- moments, cumulants
- non -Gaussian and nonstationary signal processing
- time - varying modeling and system identification.