학술논문

Inverses of Schur Parametrization Procedures for Modeling Purposes
Document Type
Conference
Source
2019 Signal Processing Symposium (SPSympo) Signal Processing Symposium (SPSympo), 2019. :86-91 Sep, 2019
Subject
Aerospace
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Technological innovation
Stochastic processes
Signal processing
Covariance matrices
Time-domain analysis
Standards
Indexes
Schur parametrization
stochastic modeling
nonlinear modeling
Language
Abstract
In this paper we present an approach to the inversion of the generalized Schur parametrization problem in accordance with Problem 1 formulated in [1]. We show that even the ’time-domain’ statement of the innovations and modeling transformations of a higher-order process is nonlinear, the associated generalized algebraic Schur parametrization as well and its inversion are purely linear (or ’multi-linear’) procedures. This result may clarify solving the nonlinear stochastic modeling problem.