284 research outputs found
Kernel Approximation on Manifolds I: Bounding the Lebesgue Constant
The purpose of this paper is to establish that for any compact, connected
C^{\infty} Riemannian manifold there exists a robust family of kernels of
increasing smoothness that are well suited for interpolation. They generate
Lagrange functions that are uniformly bounded and decay away from their center
at an exponential rate. An immediate corollary is that the corresponding
Lebesgue constant will be uniformly bounded with a constant whose only
dependence on the set of data sites is reflected in the mesh ratio, which
measures the uniformity of the data.
The analysis needed for these results was inspired by some fundamental work
of Matveev where the Sobolev decay of Lagrange functions associated with
certain kernels on \Omega \subset R^d was obtained. With a bit more work, one
establishes the following: Lebesgue constants associated with surface splines
and Sobolev splines are uniformly bounded on R^d provided the data sites \Xi
are quasi-uniformly distributed. The non-Euclidean case is more involved as the
geometry of the underlying surface comes into play. In addition to establishing
bounded Lebesgue constants in this setting, a "zeros lemma" for compact
Riemannian manifolds is established.Comment: 33 pages, 2 figures, new title, accepted for publication in SIAM J.
on Math. Ana
A unified approach to quantum dynamical maps and gaussian Wigner distributions
The KLM conditions are conditions that are necessary and sufficient for a phase-space function to be a Wigner distribution function (WDF). We apply them here to discuss three questions that have arisen recently: (1) For which WDFs P0 will the map P→P0*P be a quantum dynamical map - i.e. a map that takes WDFs to WDFs? (2) What are necessary and sufficient conditions for a phase-space gaussian to be a WDF? (3) Are there non-gaussian, non-negative WDFs? © 1988
Error estimates for interpolation of rough data using the scattered shifts of a radial basis function
The error between appropriately smooth functions and their radial basis
function interpolants, as the interpolation points fill out a bounded domain in
R^d, is a well studied artifact. In all of these cases, the analysis takes
place in a natural function space dictated by the choice of radial basis
function -- the native space. The native space contains functions possessing a
certain amount of smoothness. This paper establishes error estimates when the
function being interpolated is conspicuously rough.Comment: 12 page
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