Regularized System Identification

This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learn...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Pillonetto, Gianluigi, Chen, Tianshi, Chiuso, Alessandro, De Nicolao, Giuseppe, Ljung, Lennart
Format:	Online
Sprache:	Englisch
Veröffentlicht:	Springer Nature 2022
Schlagworte:	System Identification Machine Learning Linear Dynamical Systems Nonlinear Dynamical Systems Kernel-based Regularization Bayesian Interpretation of Regularization Gaussian Processes Reproducing Kernel Hilbert Spaces Estimation Theory Support Vector Machines Regularization Networks
Online-Zugang:	ONIX_20220620_9783030958602_20
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