Trends in spectral analysis: Higher order and cyclic statistics

Research output: Contribution to journalConference articlepeer-review


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 languageEnglish (US)
Article number1027906
Pages (from-to)74-97
Number of pages24
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Apr 28 1995
EventDigital Signal Processing Technology: A Critical Review 1995 - Orlando, United States
Duration: Apr 17 1995Apr 21 1995

Bibliographical note

Funding Information:
This work was supported by ONR Grant N0014 -93 -1 -0485.

Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.


  • cyclostationarity
  • moments, cumulants
  • non -Gaussian and nonstationary signal processing
  • polyspectra
  • time - varying modeling and system identification.


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