Matching-extrapolation of bicumulants of one-D signals using two-D AR modeling

A 2-D autoregressive (AR) model is proposed which is not based on an underlying linear process representation, for matching-extrapolation of arbitrary bicumulant sequences of one-dimensional signals. This model employs the same number of coefficients as the number of given bicumulant samples, thus, makes it possible to extrapolate a given finite set of bicumulant samples to infinity while being consistent with, i.e., matching, all of the given samples. The computation of the model coefficients requires solving a system of linear equations. An algorithm is developed for the extrapolation of the given bicumulant samples based on the proposed 2-D AR model. An example is presented to compare the performance of the proposed method with other approaches for the extrapolation of a given set of bicumulant samples