Optimization of parameters for curve interpolation by cubic splines

Abstract

a b s t r a c tIn this paper, we present an interpolation method for curves from a data set by means of the optimization of the parameters of a quadratic functional in a space of parametric cubic spline functions. The existence and the uniqueness of this problem are shown. Moreover, a convergence result of the method is established in order to justify the method presented. The aforementioned functional involves some real non-negative parameters; the optimal parametric curve is obtained by the suitable optimization of these parameters. Finally, we analyze some numerical and graphical examples in order to show the efficiency of our method.

Assessing the Best Gap-Filling Technique for River Stage Data Suitable for Low Capacity Processors and Real-Time Application Using IoT

“…To achieve this, three different customized gap-filling estimation methods with increasing processor speed requirements were taken into account. The first method adopts cubic splines [17][18][19][20][21][22][23]. The second one interpolates with radial basis functions [24][25][26][27][28][29][30].…”