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Using a natural deconvolution for analysis of perturbed integer sampling in shift-invariant spaces
Authors:Stefan Ericsson
Affiliation:Department of Mathematics, Luleå University of Technology, SE-971 87 Luleå, Sweden
Abstract:An important cornerstone of both wavelet and sampling theory is shift-invariant spaces, that is, spaces V spanned by a Riesz basis of integer-translates of a single function. Under some mild differentiability and decay assumptions on the Fourier transform of this function, we show that V also is generated by a function with Fourier transform View the MathML source for some g with View the MathML source. We explain why analysis of this particular generating function can be more likely to provide large jitter bounds ε such that any fV can be reconstructed from perturbed integer samples f(k+εk) whenever supkZ|εk|?ε. We use this natural deconvolution of View the MathML source to further develop analysis techniques from a previous paper. Then we demonstrate the resulting analysis method on the class of spaces for which g has compact support and bounded variation (including all spaces generated by Meyer wavelet scaling functions), on some particular choices of φ for which we know of no previously published bounds and finally, we use it to improve some previously known bounds for B-spline shift-invariant spaces.
Keywords:Shift-invariant space   Reproducing kernel   Interpolating function   Shift-invariant   Deconvolution   Irregular sampling   Scaling function   Shannon wavelet   Franklin   B-spline   Meyer wavelet
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