Higher-order cyclostationarity-based methods for identifying volterra systems by input-output noisy measurements

Identification methods of nonlinear Volterra systems of finite order N by input–output measurements are proposed. The input signal is assumed to be amplitude-modulated cyclostationary signal and the measures of the input and output signals are supposed to be corrupted by signal-independent additive noise. Two identification methods are proposed: the former assumes that the modulating sequence be white at least up to 2N-order; the latter considers a stationary Gaussian sequence. They exploit the higher-order cyclostationarity selectivity property of the input signal to reject noises and interferences. The performance analysis, carried out by computer simulations for a quadratic Volterra system, shows the capability of the proposed methods to operate satisfactorily in severe noise environment.