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 language||English (US)|
|Number of pages||11|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Aug 1 1991|
|Event||Optical Technology for Microwave Applications V 1991 - Orlando, United States|
Duration: Apr 1 1991 → …