Fast Algorithms for the Schur- Type Nonlinear Parametrization of Higher-Order Stochastic Processes
Agnieszka Wielgus, Jan Zarzycki · 2018
We propose a class of fast algorithms, efficiently performing nonlinear Schur parametrization of higher-order and non-Gaussian stochastic processes, following from consideration of (weak) higher-order stationarity of the underlying signals and resulting in essential nonlinear complexity reduction, allowing for their practical implementations.