On selection of maximum cumulant lags for noncausal autoregressive model fitting

Recently two techniques that use both autocorrelations and third-order autocumulants of the noisy observations were proposed by the author (1987) for the estimation of the parameters of a noncausal autoregressive (AR) signal model. In the proposed methods the maximum cumulant lag parameters were specified as large but finite. The author gives specific values for the maximum cumulant lags, and proves strong consistency of the two estimators of the AR parameters under the specified choice of lags. In addition, he develops some fundamental results concerning the recovery of the system poles from the third-order statistics of the noisy observations