On identifying Volterra transfer functions of cubically nonlinear systems using minimally sampled data

A practical method for identifying cubically nonlinear systems is presented in this paper. This method identifies the system by using the higher-order spectra of the system input and output. Compared to the conventional method, which requires the system output to be sampled at six times the bandwidth of the input, the proposed method only requires the system output to be sampled at twice the bandwidth of the system input. This greatly reduces the required computation and processing speed of the circuits. The advantage of the proposed method over the conventional one is demonstrated via computer simulation.