On the complexity of piecewise affine system identification

DOI10.1016/j.automatica.2015.09.031zbMath1329.93052arXiv1509.02348OpenAlexW2095838877MaRDI QIDQ901110

Fabien Lauer

Publication date: 23 December 2015

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.02348

zbMATH Keywords

computational complexityglobal optimizationsystem identificationpiecewise affine systemspiecewise affine regression

Mathematics Subject Classification ID

System identification (93B30) Complexity and performance of numerical algorithms (65Y20)

Related Items (9)

Global optimization for low-dimensional switching linear regression and bounded-error estimation ⋮ On the complexity of switching linear regression ⋮ Piecewise affine regression via recursive multiple least squares and multicategory discrimination ⋮ Data-driven switching modeling for MPC using regression trees and random forests ⋮ Rao-blackwellized sampling for batch and recursive Bayesian inference of piecewise affine models ⋮ Identification of hybrid and linear parameter‐varying models via piecewise affine regression using mixed integer programming ⋮ Direct data‐driven design of switching controllers ⋮ Valid inequalities for concave piecewise linear regression ⋮ Persistence of excitation for identifying switched linear systems

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