A digital technique to estimate second-order distortion usinghigher order coherence spectra

A digital spectral method for evaluating second-order distortion of a nonlinear system, which can be represented by Volterra kernels up to second order and which is subjected to a random noise input, is discussed. The importance of departures from the commonly assumed Gaussian excitation is investigated. The Hinich test is shown to be an appropriate test for orthogonality in the system identification. Tests for Gaussianity of two important sources, which are commonly used for Gaussian inputs in nonlinear system identification, are presented: (1) commercial software routines for simulation experiments, and (2) noise generators for practical experiments. The deleterious effects of assuming a Gaussian input when it is not are demonstrated. The random input method for evaluating the second-order distortion of a nonlinear system is compared with the sine-wave input method using both simulation and experimental data. The approach is applied to a loudspeaker in the low-frequency band