Approximation of exponential-type functions on a uniform grid by shifts of a basis function
This work provides theoretical advances in kernel-based interpolation for exponential-type functions, but the results are incremental and domain-specific.
The paper studies interpolation of continuous functions on a uniform grid using shifts of a kernel, focusing on Gaussian kernels. It introduces a new class of polynomials related to probabilistic Hermite polynomials and derives a closed formula for the Gaussian interpolant.
In this paper, we study the problem of interpolating a continuous function at $(n+1)$ equally-spaced points in the interval $[0,1]$, using shifts of a kernel on the $(1/n)$-spaced infinite grid. The archetypal example here is approximation using shifts of a Gaussian kernel. We present new results concerning interpolation of functions of exponential type, in particular, polynomials on the integer grid as a step en route to solve the general interpolation problem. For the Gaussian kernel we introduce a new class of polynomials, closely related to the probabilistic Hermite polynomials and show that evaluations of the polynomials at the integer points provide the coefficients of the interpolants. Taking cue from the classical Newton polynomial interpolation, we derive a closed formula for the Gaussian interpolant of a continuous function on a uniform grid in the unit interval.