Maximal-entropy driven determination of weights in least-square approximation
Numerical Analysis
2021-03-04 v3 Numerical Analysis
Abstract
We exploit the idea to use the maximal-entropy method, successfully tested in information theory and statistical thermodynamics, to determine approximating function's coefficients and squared errors' weights simultaneously as output of one single problem in least-square approximation. We provide evidence of the method's capabilities and performance through its application to representative test cases by working with polynomials as a first step. We conclude by formulating suggestions for future work to improve the version of the method we present in this paper.
Cite
@article{arxiv.2007.09429,
title = {Maximal-entropy driven determination of weights in least-square approximation},
author = {Domenico Giordano and Felice Iavernaro},
journal= {arXiv preprint arXiv:2007.09429},
year = {2021}
}
Comments
15 pages, 1 table, 10 figures. Accepted in Mathematical Methods in the Applied Sciences. Changes: fixed typo in Eq. (27)