The concept for Gaussian process model based system identification toolbox

Abstract

The Gaussian process model is an example of a flexible, probabilistic, nonparametric model with uncertainty predictions. It can be used for the modeling of complex nonlinear systems and recently it has also been used for dynamic systems identification. A need for the supporting software, in particular for dynamic system identification, has been recognised. Consequently, a Matlab toolbox concept for Gaussian Process based System Identification was generated. The use of the supporting software is illustrated with a nonlinear dynamic system identification example.

Identifiers

DOI

10.1145/1330598.1330647

Citations and references