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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 198178.0, MPI für biologische Kybernetik / Biologische Kybernetik
A case based comparison of identification with neural network and Gaussian process models.
Authors:Kocijan, J.; Banko, B.; Likar, B.; Girard, A.; Murray-Smith, R.; Rasmussen, C.E.
Editors:Ruano, E.A.
Date of Publication (YYYY-MM-DD):2003-04
Title of Proceedings:Proceedings of the International Conference on Intelligent Control Systems and Signal Processing ICONS 2003
Start Page:137
End Page:142
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:In this paper an alternative approach to black-box identification of non-linear dynamic systems is compared with the more established approach of using artificial neural networks. The Gaussian process prior approach is a representative of non-parametric modelling approaches. It was compared on a pH process modelling case study. The purpose of modelling was to use the model for control design. The comparison revealed that even though Gaussian process models can be effectively used for modelling dynamic systems caution has to be axercised when signals are selected.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:2314
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