Basis Selection for Wavelet Regression
Abstract
A wavelet basis selection procedure is presented for wavelet re(cid:173) gression. Both the basis and threshold are selected using cross(cid:173) validation. The method includes the capability of incorporating prior knowledge on the smoothness (or shape of the basis functions) into the basis selection procedure. The results of the method are demonstrated using widely published sampled functions. The re(cid:173) sults of the method are contrasted with other basis function based methods.
Cite
Text
Wheeler and Dhawan. "Basis Selection for Wavelet Regression." Neural Information Processing Systems, 1998.Markdown
[Wheeler and Dhawan. "Basis Selection for Wavelet Regression." Neural Information Processing Systems, 1998.](https://mlanthology.org/neurips/1998/wheeler1998neurips-basis/)BibTeX
@inproceedings{wheeler1998neurips-basis,
title = {{Basis Selection for Wavelet Regression}},
author = {Wheeler, Kevin R. and Dhawan, Atam P.},
booktitle = {Neural Information Processing Systems},
year = {1998},
pages = {627-633},
url = {https://mlanthology.org/neurips/1998/wheeler1998neurips-basis/}
}