Multidimensional spline integration of scattered data

Endrödi G (2011)
Computer Physics Communications 182(6): 1307-1314.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
We introduce a numerical method for reconstructing a multidimensional surface using the gradient of the surface measured at some values of the coordinates. The method consists of defining a multidimensional spline function and minimizing the deviation between its derivatives and the measured gradient. Unlike a multidimensional integration along some path, the present method results in a continuous, smooth surface, furthermore, it also applies to input data that are non-equidistant and not aligned on a rectangular grid. Function values, first and second derivatives and integrals are easy to calculate. The proper estimation of the statistical and systematical errors is also incorporated in the method.
Erscheinungsjahr
2011
Zeitschriftentitel
Computer Physics Communications
Band
182
Ausgabe
6
Seite(n)
1307-1314
ISSN
00104655
Page URI
https://pub.uni-bielefeld.de/record/2955768

Zitieren

Endrödi G. Multidimensional spline integration of scattered data. Computer Physics Communications. 2011;182(6):1307-1314.
Endrödi, G. (2011). Multidimensional spline integration of scattered data. Computer Physics Communications, 182(6), 1307-1314. https://doi.org/10.1016/j.cpc.2011.03.009
Endrödi, Gergely. 2011. “Multidimensional spline integration of scattered data”. Computer Physics Communications 182 (6): 1307-1314.
Endrödi, G. (2011). Multidimensional spline integration of scattered data. Computer Physics Communications 182, 1307-1314.
Endrödi, G., 2011. Multidimensional spline integration of scattered data. Computer Physics Communications, 182(6), p 1307-1314.
G. Endrödi, “Multidimensional spline integration of scattered data”, Computer Physics Communications, vol. 182, 2011, pp. 1307-1314.
Endrödi, G.: Multidimensional spline integration of scattered data. Computer Physics Communications. 182, 1307-1314 (2011).
Endrödi, Gergely. “Multidimensional spline integration of scattered data”. Computer Physics Communications 182.6 (2011): 1307-1314.
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