The samples included in the average can be an arbitrary subset of all the samples in the signal (e.g., samples within a finite time window or a sub-sampling of one of the signals). For a large number of samples, the average converges to the true covariance. Cross-covariance may also refer to a "deterministic" cross-covariance between two signals. This consists of summing over "all" time indices. For example, for discrete-time signals formula_36 and formula_37 the cross-covariance is defined as  where the line indicates that the complex conjugate is taken when the signals are complex-valued. For continuous functions formula_39 and formula_40 the (deterministic) cross-covariance is defined as  The (deterministic) cross-covariance of two continuous signals is related to the convolution by  and the (deterministic) cross-covariance of two discrete-time signals is related to the discrete convolution by