Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Analysis of some methods for reduced rank gaussian process regression
Switching and Learning in Feedback Systems
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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.