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

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.