Optimal sample length for calculating transfer functions from discrete experimental data

Abstract

Transfer functions are useful tools in observing the behaviour of non-linear systems. Transfer functions convert an input signal into an output signal, and for non-linear systems can be calculated separately for each order of response using the Volterra series. The Volterra series quantifies the linear and non-linear responses separately for systems with either Gaussian or non-Gaussian inputs, and is particularly useful when calculating transfer functions from experimental data, as the calculations can be performed using a discrete frequency domain format. The application of the Volterra series to discrete experimental data requires careful consideration of various factors that impact on the..