A new stable feedback ladder algorithm for the identification of moving average processes

A novel algorithm for the direct identification of the coefficients of a moving average model is presented. The scheme can be represented in a feedback ladder form, recursive in time and order, hence allowing sequential processing of data observed from a process. Potential applications are numerous in different fields such as spectral estimation, automatic control or econometrics. The paper briefly discusses the underlying principles of the method. Results from simulations are included in order to display the general behaviour of the algorithm and its sensitivity to uncertainty in the model order.