Regularized system identification. Learning dynamic models from data
type: Item
instance of: scholarly article
title: Regularized system identification. Learning dynamic models from data
zbMATH Open document ID: 1506.93002
DOI: 10.1007/978-3-030-95860-2
author: Gianluigi Pillonetto
author: Tianshi Chen
author: Alessandro Chiuso
author: Lennart Ljung
author: Giuseppe De Nicolao
published in: Communications and Control Engineering
publication date: 2022-03-11T00:00:00Z
review text: This monograph focuses on comprehensive overview of the most common type of the inverse problems: system identification (SI). It organized as follows. First, authors introduce the SI's roots from statistical theory dealing with classic system identification, and introduce the general tools and terms such bias, variance, cross-validation as well as black-box and gray-box models. Next, regularization of linear regression models is considered with focus mainly on the least squares method and its regularization. Next chapter deals with Bayesian interpretation of regularization including popular Markov chain Monte Carlo estimation. Then, after historical introduction and motivation for regularization methods for linear system identification (in ``classical'' mean square error perspective), authors focuses on the linear system identification and regularization in reproducing kernel Hilbert spaces and support vector machines. Here the special attention is paid to kernels examples. Finally, before moving to cases studies, authors deals with regularization for nonlinear system identification. The special attention is paid to the Bayesian estimation of Gaussian random fields, Volterra and deep learning models of nonlinear dynamical systems. Finally, numerical experiments and real world cases (including biomedical and mechanics applications) are discussed.
Mathematics Subject Classification ID: 93-02
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93C05
Mathematics Subject Classification ID: 93C10
zbMATH DE Number: 7488353
zbMATH Keywords: system identification
zbMATH Keywords: regularization
zbMATH Keywords: Bayesian inference
zbMATH Keywords: RKHS
zbMATH Keywords: SVM
zbMATH Keywords: ARMAX
zbMATH Keywords: Volterra models regularization
reviewed by: Denis Sidorov
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-3-030-95860-2
OpenAlex ID: W4285265010
description: scientific article; zbMATH DE number 7488353