Fast Algorithms for the Schur- Type Nonlinear Parametrization of Higher-Order Stochastic Processes

Wielgus, Agnieszka; Zarzycki, Jan

doi:10.23919/eusipco.2018.8553017

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2018

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“…allowing for a considerable complexity reduction in a uniform way. The results presented here are a good starting point and prove to be useful for nonlinear generalizations to higher-order near-stationary stochastic processes, treated in [22], as complexity in the general nonlinear Schur parametrization problem solution becomes an essential constraint in the resulting algorithms efficient implementations so that complexity reduction is of crucial importance in that case.…”

Section: Introductionmentioning

confidence: 91%