In this document we propose the use of a widely known learning-from-examples paradigm, namely the Support Vector Machines for Regression (SVRs), for system identification problems. We start off with the identification of a simple linear system taken from the literature, and proceed with the non-linear case as a second step.
Support Vector Machines for System Identification
Marconato, Anna;Gubian, Michele;Boni, Andrea;Petri, Dario
2007-01-01
Abstract
In this document we propose the use of a widely known learning-from-examples paradigm, namely the Support Vector Machines for Regression (SVRs), for system identification problems. We start off with the identification of a simple linear system taken from the literature, and proceed with the non-linear case as a second step.File in questo prodotto:
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