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Lebesgue functions and Lebesgue constants in polynomial interpolation
Journal of Inequalities and Applications, 2016 The Lebesgue constant is a valuable numerical instrument for linear interpolation because it provides a measure of how close the interpolant of a function is to the best polynomial approximant of the function.
B Ali Ibrahimoglu
exaly +3 more sources
Optimal interpolation methods for predicting groundwater levels in Abu Dhabi Emirate using ArcGIS [PDF]
Scientific ReportsThis research aimed to determine the optimal interpolation methods for predicting unsampled groundwater levels in Abu Dhabi Emirate, UAE. Geostatistical and deterministic interpolation techniques including Inverse Distance Weighting, Ordinary Kriging ...
Tala Maksoud +2 more
doaj +2 more sources
On Polynomial Interpolation in the Monomial Basis
SIAM Journal on Numerical Analysis31 pages, 17 figures. Accepted by SIAM J.
Kirill Serkh, Zewen Shen
exaly +5 more sources
Smooth polynomial interpolation to boundary data on triangles [PDF]
, 1973 Boolean sum interpolation theory is used to derive a polynomial interpolant which interpolates a function F ∈ CN(∂T), and its derivatives of order N and less, on the boundary 3T of a triangle T.
Gregory, JA, Barnhill, RE
core +6 more sources
Symmetric smooth interpolation on triangles [PDF]
, 1974 Rational and polynomial 'smooth' interpolation schemes are derived which interpolate a function and its derivatives along the boundary of a triangle.
Gregory, JA
core +6 more sources
Assessment of spatial interpolation techniques for drought severity analysis in Salt Lake Basin [PDF]
Desert, 2021 Drought risk management requires drought monitoring which is usually carried out by applying different drought indices which are, effectively, continuous functions of precipitation and other meteorological data.
Amir R. Keshtkar, N. Moazami, A. Afzali
doaj +1 more source
Joint motion planning of industrial robot based on hybrid polynomial interpolation
Xibei Gongye Daxue Xuebao, 2022 To plan an industrial robot's point-to-point joint motion that has velocity constraints, the cubic polynomial interpolation planning method has angular acceleration discontinuity.
PU Yasong +4 more
doaj +1 more source
Interpolation with the polynomial kernels
CoRR, 2022 The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their lack of strict positive definiteness.
Elefante G. +5 more
openaire +8 more sources
Polynomial Interpolation on Sequences
Mathematica Pannonica, 2022 This short note deals with polynomial interpolation of complex numbers verifying a Lipschitz condition, performed on consecutive points of a given sequence in the plane. We are interested in those sequences which provide a bound of the error at the first uninterpolated point, depending only on its distance to the last interpolated one.
Tugores, Francesc, Tugores, Laia
openaire +1 more source
TOPOLOGICAL 3D ELEVATION DATA INTERPOLATION OF ASTER GDEM BASED ON CONTINUOUS DEFORMATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 In Geographic Information Science, polynomial methods such as linear estimation and non-polynomial methods including Inverse Distance Weighting and Kriging have been used for elevation data interpolation. In this paper, 3D data interpolation using linear
A. Jamali, F. A. Castro
doaj +1 more source