Symmetric Canonical Polyadic Decomposition And Gauss-Newton Optimizer For Nonlinear Volterra System Identification

Master thesis (2022)

Authors

Z. LI Mechanical Engineering

Contributors

K. Batselier Team Kim Batselier - Mechanical, Maritime and Materials Engineering (supervisor 1)
Faculty
Mechanical Engineering
Copyright: © 2022 Zhehan LI
Tensor decomposition Gauss-Newton Nonlinear identification
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Published Date

27-07-2022

Language

English

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Faculty

Mechanical Engineering

Abstract

This thesis applies the Gauss-Newton optimizer to estimate the parameter values of the Volterra-PARAFAC model by minimizing a nonlinear least square cost (NLS) function given the input and output measurements of the MISO Volterra system.