Summary
2011 International Symposium on Nonlinear Theory and Its Applications
2011
Session Number:A4L-D
Session:
Number:A4L-D3
Gaussian Process Models Trained by Particle Swarm Optimization for Continuous-Time Nonlinear System Identification
Tomohiro Hachino, Shinichiro Yoneda, Hitoshi Takata,
pp.278-281
Publication Date:2011/9/4
Online ISSN:2188-5079
Summary:
This paper proposes a nonparametric identification of continuous-time nonlinear systems by using a Gaussian process (GP) model. The GP prior model is trained by particle swarm optimization. The nonlinear function of the objective system is estimated as the predictive mean function of the GP, and the confidence measure of the estimated nonlinear function is given by the predictive covariance of the GP.