Estimation of non-stationary moving-average models
Yves Grenier · 2005
This paper describes two methods for time-dependent moving-average modelling of non-stationary signals. In both of them, the finite-order MA model is approximated by an infinite-order auto-re gressive model. In the second one, the use of the AR model is explicit : by means of the inversion of this model, the innovation is estimated and the MA model is then obtained by a least-square procedure. In the first method, the AR model is implicit : a vector signal is associated to the scalar one, and the MA algorithm contains two steps : Schur parametrization of an estimate of the covariance of the vector process, followed by a reduction of the vector model to a scalar one.