  We demonstrate the capabilities of nonlinear Volterra models to simulate the
behavior of an audio system and compare them to linear filters. In this paper a
nonlinear model of an audio system based on Volterra series is presented and
Normalized Least Mean Square algorithm is used to determine the Volterra series
to third order. Training data for the models were collected measuring a
physical speaker using a laser interferometer. We explore several training
signals and filter's parameters. Results indicate a decrease in Mean Squared
Error compared to the linear model with a dependency on the particular test
signal, the order and the parameters of the model.
