The Interpolation Theory of Radial Basis Functions

In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 2$. Specifically, for every $p > 2$, we construct a set of different points in some $\Rd$ for which the interpolation matrix is singular. The greater part of this work investigates the sensitivity of radial basis function interpolants to changes in the function values at the interpolation points. Our early results show that it is possible to recast the work of Ball, Narcowich and Ward in the language of distributional Fourier transforms in an elegant way. We then use this language to study the interpolation matrices generated by subsets of regular grids. In particular, we are able to extend the classical theory of Toeplitz operators to calculate sharp bounds on the spectra of such matrices. Applying our understanding of these spectra, we construct preconditioners for the conjugate gradient solution of the interpolation equations. Our main result is that the number of steps required to achieve solution of the linear system to within a required tolerance can be independent of the number of interpolation points. The Toeplitz structure allows us to use fast Fourier transform techniques, which imp lies that the total number of operations is a multiple of $n \log n$, where $n$ is the number of interpolation points. Finally, we use some of our methods to study the behaviour of the multiquadric when its shape parameter increases to infinity. We find a surprising link with the {\it sinus cardinalis} or {\it sinc} function of Whittaker. Consequently, it can be highly useful to use a large shape parameter when approximating band-limited functions.

[1]  R. Poeckert,et al.  Warping digital images using thin plate splines , 1993, Pattern Recognit..

[2]  J. G. Hayes Fitting surfaces to data , 1987 .

[3]  I. J. Schoenberg On Certain Metric Spaces Arising From Euclidean Spaces by a Change of Metric and Their Imbedding in Hilbert Space , 1937 .

[4]  M. J. D. Powell Univariate Multiquadric Interpolation: Some Recent Results , 1991, Curves and Surfaces.

[5]  K. BeatsonR.,et al.  Fast Evaluation of Radial Basis Functions , 1998 .

[6]  P. Revesz Interpolation and Approximation , 2010 .

[7]  Amara Lynn Graps,et al.  An introduction to wavelets , 1995 .

[8]  B. Baxter On the Asymptotic Cardinal Function of the Multiquadric '(r) = (r 2 + C 2 ) 1=2 as C ! 1 , 2022 .

[9]  W. R. Madych Polyharmonic Splines, Multiscale Analysis, and Entire Functions , 1990 .

[10]  B. Baxter,et al.  Conditionally positive functions andp-norm distance matrices , 1991, 1006.2449.

[11]  M. Buhmann Multivariate cardinal interpolation with radial-basis functions , 1990 .

[12]  R. Franke Scattered data interpolation: tests of some methods , 1982 .

[13]  Richard Franke,et al.  Recent Advances in the Approximation of surfaces from scattered Data , 1987, Topics in Multivariate Approximation.

[14]  C. Micchelli,et al.  Multiply monotone functions for cardinal interpolation , 1991 .

[15]  Martin D. Buhmann,et al.  Error Estimates for Multiquadric Interpolation , 1991, Curves and Surfaces.

[16]  Norm estimates for inverses of distance matrices , 1992 .

[17]  J. H. Wilkinson The algebraic eigenvalue problem , 1966 .

[18]  S. Rippa,et al.  Numerical Procedures for Surface Fitting of Scattered Data by Radial Functions , 1986 .

[19]  M. Powell,et al.  Approximation theory and methods , 1984 .

[20]  E. Hille,et al.  Analytic Function Theory. Volume II , 1973 .

[21]  I. J. Schoenberg Metric spaces and completely monotone functions , 1938 .

[22]  R. Jackson Inequalities , 2007, Algebra for Parents.

[23]  Nira Dyn,et al.  Interpolation by piecewise-linear radial basis functions, II , 1989 .

[24]  R. Fletcher Practical Methods of Optimization , 1988 .

[25]  Will Light,et al.  Approximation Theory in Tensor Product Spaces , 1985 .

[26]  C. Micchelli,et al.  Recent Progress in multivariate splines , 1983 .

[27]  F. J. Narcowich,et al.  Norms of inverses and condition numbers for matrices associated with scattered data , 1991 .

[28]  I. R. H. Jackson Radial basis function methods for multivariable approximation , 1988 .

[29]  R. E. Carlson,et al.  Improved accuracy of multiquadric interpolation using variable shape parameters , 1992 .

[30]  C. Micchelli,et al.  On multivariate -splines , 1989 .

[31]  W. Madych,et al.  Polyharmonic cardinal splines , 1990 .

[32]  Bradley John Charles Baxter,et al.  Norm estimates for thel2-inverses of multivariate Toeplitz matrices , 1994, Numerical Algorithms.

[33]  E. Stein,et al.  Introduction to Fourier Analysis on Euclidean Spaces. , 1971 .

[34]  Edmund Taylor Whittaker,et al.  A Course of Modern Analysis , 2021 .

[35]  Xingping Sun Norm estimates for inverses of Euclidean distance matrices , 1992 .

[36]  I. J. Schoenberg,et al.  Fourier integrals and metric geometry , 1941 .

[37]  L. Schwartz Théorie des distributions , 1966 .

[38]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.

[39]  S. Rippa,et al.  Data Dependent Triangulations for Piecewise Linear Interpolation , 1990 .

[40]  D. S. Jones The theory of generalised functions: Table of Laplace transforms , 1982 .