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Galvão, R. K. H. and Becerra, V. M. (2002) Linear-wavelet models for system identification. In: 15th Triennial World Congress of the International Federation of Automatic Control (IFAC), 21-26 Jul 2002, Barcelona, Spain.
Abstract/Summary
A model structure comprising a wavelet network and a linear term is proposed for nonlinear system identification. It is shown that under certain conditions wavelets are orthogonal to linear functions and, as a result, the two parts of the model can be identified separately. The linear-wavelet model is compared to a standard wavelet network using data from a simulated fermentation process. The results show that the linear-wavelet model yields a smaller modelling error when compared to a wavelet network using the same number of regressors.
| Item Type | Conference or Workshop Item (Paper) |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/19238 |
| Refereed | Yes |
| Divisions | Science |
| Uncontrolled Keywords | neural-network models, system identification, nonlinear models, function approximation, non-parametric identification, fermentation processes |
| Download/View statistics | View download statistics for this item |
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