@Article{ATA-29-169,
author = {D. Costarelli and R. Spigler},
title = {Constructive Approximation by Superposition of Sigmoidal Functions},
journal = {Analysis in Theory and Applications},
year = {2013},
volume = {29},
number = {2},
pages = {169--196},
abstract = {<p style="text-align: justify;">In this paper, a constructive theory is developed for approximating functions of one or more variables by superposition of sigmoidal functions. This is done in the uniform norm as well as in the $L^p$ norm. Results for the simultaneous approximation, with the same order of accuracy, of a function and its derivatives (whenever these exist), are obtained. The relation with neural networks and radial basis functions approximations is discussed. Numerical examples are given for the purpose of illustration.</p>},
issn = {1573-8175},
doi = {https://doi.org/10.4208/ata.2013.v29.n2.8},
url = {http://global-sci.org/intro/article_detail/ata/4525.html}
}