Shift-Invariant and Sampling Spaces Associated With the Fractional Fourier Transform Domain


Shift-invariant spaces play an important role in sampling theory, multiresolution analysis, and many other areas of signal and image processing. A special class of the shift-invariant spaces is the class of sampling spaces in which functions are determined by their values on a discrete set of points. One of the vital tools used in the study of sampling spaces is the Zak transform. The Zak transform is also related to the Poisson summation formula and a common thread between all these notions is the Fourier transform. In this paper, we extend some of these notions to the fractional Fourier transform (FrFT) domain. First, we introduce two definitions of the discrete fractional Fourier transform and two semi-discrete fractional convolutions associated with them. We employ these definitions to derive necessary and sufficient conditions pertaining to FrFT domain, under which integer shifts of a function form an orthogonal basis or a Riesz basis for a shift-invariant space. We also introduce the fractional Zak transform and derive two different versions of the Poisson summation formula for the FrFT. These extensions are used to obtain new results concerning sampling spaces, to derive the reproducing-kernel for the spaces of fractional band-limited signals, and to obtain a new simple proof of the sampling theorem for signals in that space. Finally, we present an application of our shift-invariant signal model which is linked with the problem of fractional delay filtering.

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