Sep 30, 2007 · Abstract: A Bayesian Gaussian process (GP) modeling approach has recently been introduced to model-based control strategies.
A novel algorithm for network structure optimization, based on the estimate of the uncertainties of individual local LGP models, is proposed in Section VI. In.
The proposed methodology combines the local model network principle with the GP prior approach, and a novel algorithm for structure determination and ...
A local linear GP model network is proposed in this paper. The proposed methodology combines the local model network principle with the GP prior approach.
In this paper the focus is on GP with incorporated local models as the approach which could replace local models network.
The proposed methodology combines the local model network principle with the GP prior approach. A novel algorithm for structure determination and optimization ...
Abstract— The paper describes the identification of nonlinear dynamic systems with a Gaussian process prior model. This approach is an example of a ...
People also ask
What is the Gaussian process identification?
What is local approximate Gaussian process?
Are neural networks Gaussian processes?
What is a Gaussian process model?
G. Gregorčič et al. Local model network identification with Gaussian processes. IEEE Transactions on Neural Networks. (2007).
A common approach in this situation is to build local models using the data in the vicinity of equilibrium points and then blend these models so as to obtain a ...
The proposed methodology combines the local model network principle with the GP prior approach. A novel algorithm for structure determination and optimization ...