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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
W. Xiao; A. Lederer; S. Hirche 
Title:
Learning Stable Nonparametric Dynamical Systems with Gaussian Process Regression 
Abstract:
Modelling real world systems involving humans such as biological processes for disease treatment or human behavior for robotic rehabilitation is a challenging problem because labeled training data is sparse and expensive, while high prediction accuracy is required from models of these dynamical systems. Due to the high nonlinearity of problems in this area, data-driven approaches gain increasing attention for identifying nonparametric models. In order to increase the prediction performance of th...    »
 
Keywords:
data_driven_control; rehyb 
Book / Congress title:
Proceedings of the 21st IFAC World Congress 
Year:
2020 
Year / month:
2020-07