Normalized 2-D ARMA lattice parameter modeling algorithm

Abstract

A Levinson-type algorithm is proposed for estimating the two-dimensional autoregressive-moving average (ARMA) model from the observed inputs and outputs of an unknown 2-D system. By applying the concept of dummy prediction errors, the algorithm can be extended for computing 2-D models of any AR-order and MA-order. It is shown that the algorithm can be greatly simplified when the input is a white process.<>