Parametric identification of systems using a frequency slice of the bispectrum

A parametric approach, based on sums of cumulants, is proposed for the identification of linear shift-invariant systems. The identification of the autoregressive parameters of the system is related to the rational approximation of a frequency slice of the output bispectrum. For a causal or a noncausal system it is shown that it is sufficient to solve Hankel-type matrix equations. The procedure can be efficiently implemented by means of recursive Pade approximants or modified least-squares rational approximations algorithms. The moving-average parameters of the system are calculated by solving some nonlinear equations. Examples illustrating the procedure and its advantages are given