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.
|Title of host publication||International Joint Conference on Neural Networks: IJCNN 2002|
|Number of pages||6|
|Publication status||Published - 1 May 2002|
- linear-wavelet models, nonlinear identification, nonlinear regression structure, pressure plant, radial wavelets, system identification, wavelet network