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.
Smoothing exponential-polynomial splines for multiexponential decay data
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
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Dolomites Research Notes on Approximation
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