Support Vector Machines for System Identification

Marconato, Anna and Gubian, Michele and Boni, Andrea and Petri, Dario (2007) Support Vector Machines for System Identification. UNSPECIFIED. (Unpublished)

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    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.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
    Uncontrolled Keywords: Support Vector Machines, system identification
    Report Number: DIT-07-023
    Repository staff approval on: 07 Jun 2007

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