Preprint 29/2005

Low-Rank Kronecker-Product Approximation to Multi-Dimensional Nonlocal Operators. Part I. Separable Approximation of Multi-Variate Functions

Wolfgang Hackbusch and Boris N. Khoromskij

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Submission date: 14. Apr. 2005 (revised version: September 2005)
Pages: 22
published in: Computing, 76 (2006) 3/4, p. 177-202 
DOI number (of the published article): 10.1007/s00607-005-0144-0
MSC-Numbers: 65F50, 65F30, 46B28, 47A80
Keywords and phrases: hierarchical matrices, kronecker tensor-product, sinc interpolation, sinc quadrature, approximation by exponential sums
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The Kronecker tensor-product approximation combined with the formula20-matrix techniques provides an efficient tool to represent integral operators as well as certain functions F(A) of a discrete elliptic operator A in formula26 with a high spatial dimension d. In particular, we approximate the functions formula30 and sign(A) of a finite difference discretisation formula34 with a rather general location of the spectrum. The asymptotic complexity of our data-sparse representations can be estimated by formula36, p=1,2, with q independent of d, where formula44 is the dimension of the discrete problem in one space direction. In this paper (Part I), we discuss several methods of a separable approximation of multi-variate functions. Such approximations provide the base for a tensor-product representation of operators. We discuss the asymptotically optimal sinc quadratures and sinc interpolation methods as well as the best approximations by exponential sums. These tools will be applied in Part II continuing this paper to the problems mentioned above.

18.10.2019, 02:12