Linear-wavelet models for non-linear identification applied to a pressure plantBecerra, 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, https://doi.org/10.1109/IJCNN.2002.1007479. 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/SummaryA 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.
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