Nonlinear system identification with regularized tensor network B-splines

DOI10.1016/j.automatica.2020.109300zbMath1453.93063arXiv2003.07594OpenAlexW3093317881MaRDI QIDQ2208614

Ridvan Karagoz, Kim Batselier

Publication date: 3 November 2020

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2003.07594

zbMATH Keywords

B-splinesNARXcurse of dimensionalitynonlinear system identificationtensor network

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Spline approximation (41A15)

Related Items (3)

Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory ⋮ An efficient recursive identification algorithm for multilinear systems based on tensor decomposition ⋮ ExSpliNet: An interpretable and expressive spline-based neural network

Uses Software

• Matlab

Cites Work

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