Correlation and Covariance

Correlation and covariance (which is correlation with any non-zero mean values of the signals removed beforehand) are closely related to convolution. They are useful in analyzing signals with random components. Autocorrelation and autocovariance of signals are computed with the A_CORRELATE function, and crosscorrelation and crosscovariance are computed with the C_CORRELATE function. See Time-Series Analysis for details.