Accessibility navigation


Linear-wavelet models for non-linear identification applied to a pressure plant

Becerra, V. M., Galvão, R. K. H., Calado, J. M. F. and Silva, P. M. (2002) Linear-wavelet models for non-linear identification applied to a pressure plant. In: International Joint Conference on Neural Networks: IJCNN 2002, 12-17 May 2002, Honolulu, HI, USA, pp. 2180-2185.

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1109/IJCNN.2002.1007479

Abstract/Summary

A nonlinear regression structure comprising a wavelet network and a linear term is proposed for system identification. The theoretical foundation of the approach is laid by proving that radial wavelets are orthogonal to linear functions. A constructive procedure for building such models is described and the approach is tested with experimental data.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science
ID Code:19198
Uncontrolled Keywords:linear-wavelet models, nonlinear identification, nonlinear regression structure, pressure plant, radial wavelets, system identification, wavelet network

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation