Shift-Invariant and Sampling Spaces Associated with the Special Affine Fourier Transform

TL;DR

This paper extends classical sampling and shift-invariant space results to the Special Affine Fourier Transform (SAFT) domain, providing theoretical foundations and practical applications like fractional delay filtering.

Contribution

It demonstrates that key sampling theorems and shift-invariant space properties hold in the SAFT domain, generalizing prior Fourier-based results.

Findings

Shannon's sampling theorem is valid in the SAFT domain.

Sampling in the SAFT domain corresponds to orthogonal projection onto bandlimited subspaces.

The paper introduces a least-squares optimal sampling approach and applies it to fractional delay filtering.

Abstract

The Special Affine Fourier Transformation or the SAFT generalizes a number of well known unitary transformations as well as signal processing and optics related mathematical operations. Shift-invariant spaces also play an important role in sampling theory, multiresolution analysis, and many other areas of signal and image processing. Shannon's sampling theorem, which is at the heart of modern digital communications, is a special case of sampling in shift-invariant spaces. Furthermore, it is well known that the Poisson summation formula is equivalent to the sampling theorem and that the Zak transform is closely connected to the sampling theorem and the Poisson summation formula. These results have been known to hold in the Fourier transform domain for decades and were recently shown to hold in the Fractional Fourier transform domain by A. Bhandari and A. Zayed. The main goal of this article is to show that these results also hold true in the SAFT domain. We provide a short, self-contained proof of Shannon's theorem for functions bandlimited in the SAFT domain and then show that sampling in the SAFT domain is equivalent to orthogonal projection of functions onto a subspace of bandlimited basis associated with the SAFT domain. This interpretation of sampling leads to least-squares optimal sampling theorem. Furthermore, we show that this approximation procedure is linked with convolution and semi-discrete convolution operators that are associated with the SAFT domain. We conclude the article with an application of fractional delay filtering of SAFT bandlimited functions.