Acousto-optic estimation of autocorrelation and spectra using triple-correlations and bispectra

Brian M. Sadler, Georgios B. Giannakis, Dale J. Smith

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Non-parametric estimation of lower-order statistics from higher-order statistics of continuous processes is considered. Of particular interest is estimation of correlations and spectra (second-order statistics) from higher-order correlations and polyspectra (higherorder statistics). The use of higher-order statistics is motivated by their insensitivity to a wide class of additive noises including Gaussian noise of unknown covariance. The fact that lower-order correlations are projections of higher-order correlations is exploited. Experimental results are presented using an acousto-optic triple product processor to estimate the autocorrelation of a 1-d signal.

Original languageEnglish (US)
Pages (from-to)246-256
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Aug 1 1991
Externally publishedYes
EventOptical Technology for Microwave Applications V 1991 - Orlando, United States
Duration: Apr 1 1991 → …

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