Identification of polyperiodic Volterra systems by means of input–output noisy measurements

Abstract

Identification methods of polyperiodically time-varying Volterra systems of finite order N by input–output measurements are proposed. The presence of additive signal-independent noise on the system input and output signal measurements is taken into account. Two identification methods are presented: both assume that the input signal be amplitude-modulated cyclostationary signal. The former supposes that the modulating sequence be white at least up to 2 N-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 periodically time-varying quadratic Volterra system, shows the capability of the proposed methods to operate satisfactorily in severe noise environments.