Abstract
In many applications, the definition of fitting models that mimic the behaviour of experimental data is a challenging issue. In this paper a data-driven approach to represent (multi)exponential decay data is presented. We propose a fitting model based on smoothing splines defined by means of a differential operator. To solve the linear system involved in the smoothing exponential-polynomial spline definition, the main idea is to define B-spline like functions for the spline space, that are locally represented by Bernstein-like bases through Hermite interpolation conditions.
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Conti C., Campagna R., Cuomo S. (2019) "Smoothing exponential-polynomial splines for multiexponential decay data
" Dolomites Research Notes on Approximation, 12(1), 86-100. DOI: 10.14658/PUPJ-DRNA-2019-1-9
Year of Publication
2019
Journal
Dolomites Research Notes on Approximation
Volume
12
Issue Number
1
Start Page
86
Last Page
100
Date Published
09/2019
ISSN Number
2035-6803
Serial Article Number
9
DOI
10.14658/PUPJ-DRNA-2019-1-9
Issue
Section
Articles