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arXiv:2611.12326 · v1

Tensor Network Kernel Machines for Nonlinear System Identification

Kim Batselier
eess.SYcs.LGmath.OC
首次提交 2026-11-09 20:46
版本更新 2026-11-09 20:46
雷达观测 2026-11-10 15:22
arXiv ↗PDF ↗

摘要

Over the past ten years Tensor Network Kernel Machines have enabled efficient nonlinear system identification through the use of low-rank tensor networks. The goal of this article is to provide the reader with a basic understanding of this model class in terms of its two defining properties. Furthermore, both the optimization and regularization of such models are discussed, together with recent developments and starting points for further exploration.

作者备注：This work has been submitted to IFAC for possible publication

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v1 · 2026-11-09 20:46 · 最新观测版本

Tensor Network Kernel Machines for Nonlinear System Identification

Over the past ten years Tensor Network Kernel Machines have enabled efficient nonlinear system identification through the use of low-rank tensor networks. The goal of this article is to provide the reader with a basic understanding of this model class in terms of its two defining properties. Furthermore, both the optimization and regularization of such models are discussed, together with recent developments and starting points for further exploration.

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