Efficient Schur parametrization of near-stationary stochastic processes

We present efficient Schur parametrization algorithms for a subclass of near-stationary second-order stochastic processes which we call p-stationary processes. This approach allows for complexity reduction of the general linear Schur algorithm in a uniform way and results in a hierachical class of the algorithms, suitable for efficient implementations, being a good starting point for nonlinear generalizations.