A Sampling Principle Associated with Saitoh’s Fundamental Theory of Linear Transformations

  • J. R. Higgins
Part of the International Society for Analysis, Applications and Computation book series (ISAA, volume 9)

Abstract

A more general form of a sampling theorem due to Saitoh is given, to the effect that members of certain reproducing kernel Hilbert function spaces are recoverable from samples via a sampling series. This series can be viewed as a discrete form of reproducing equation. The ‘information loss error’ associated with this series expansion is discussed.

The sampling principle of Kramer is generalized in this context, and several examples are given where the kernels arise from polynomials of Meixner type.

Keywords

Hilbert Space Orthogonal Basis Sampling Theorem Sampling Theory Reconstruction Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • J. R. Higgins
    • 1
  1. 1.Anglia Polytechnic UniversityCambridgeEngland

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