Spline Methods Using Low Discrepancy Designs

نویسندگان

  • Xiaoyan Zeng
  • Peter Kritzer
  • Fred J. Hickernell
چکیده

Splines are minimum-norm approximations of functions that interpolate the given data, (xl, f(xl)), l = 0, . . . , N − 1. In this paper, we consider the problem of approximating functions in certain reproducing kernel Hilbert spaces, with special choices of the points xl, l = 0, . . . , N−1. The designs considered here are node sets of integration lattices and digital nets for functions f defined over the unit cube. The worst case errors (in the L∞ norm) of the splines are shown to depend on the smoothness of the functions being approximated.

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تاریخ انتشار 2008