Univariate interpolation by exponential functions and Gaussian RBFs for generic sets of nodes (Q1935761)

Among the various tools for functional interpolation and approximation, the approach using radial basis functions stands out as usable also in higher dimensions and for many data, and also because in many cases very accurate approximations are obtainable. In this paper, the approach is exemplified by the one-dimensional setting and exponential convergence orders are established for suitable approximants. In particular, the frequently used Gaussian radial basis function (Gauß kernel) is applied in the approximation results.