Symmetric Canonical Polyadic Decomposition And Gauss-Newton Optimizer For Nonlinear Volterra System Identification
Z. LI (TU Delft - Mechanical Engineering)
K. Batselier – Mentor (TU Delft - Mechanical Engineering)
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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.