Subspaces with extra invariance nearest to observed data

TL;DR

This paper develops a method to find the smallest shift-invariant subspace with extra invariance properties that best approximates given data in L2(Rd), with applications to jitter error and connections to Paley-Wiener spaces.

Contribution

It introduces a construction for the optimal small shift-invariant space with extra invariance, including explicit error expression and a Parseval frame, extending approximation theory in L2(Rd).

Findings

Constructed the closest shift-invariant space with extra invariance to given data.

Derived an explicit error formula for the approximation.

Connected shift-invariant spaces with multi-tile sets and Riesz bases.

Abstract

Given an arbitrary finite set of data F= {f_1,..., f_m} in L2(Rd) we prove the existence and show how to construct a "small shift invariant space" that is "closest" to the data F over certain class of closed subspaces of L2(Rd). The approximating subspace is required to have extra-invariance properties, that is to be invariant under translations by a prefixed additive subgroup of Rd containing Zd. This is important for example in situations where we need to deal with jitter error of the data. Here small means that our solution subspace should be generated by the integer translates of a small number of generators. We give an expression for the error in terms of the data and construct a Parseval frame for the optimal space. We also consider the problem of approximating F from generalised Paley-Wiener spaces of Rd that are generated by the integer translates of a finite number of functions. That is finitely generated shift invariant spaces that are translation invariant. We characterise these spaces in terms of multi-tile sets of Rd, and show the connections with recent results on Riesz basis of exponentials on bounded sets of Rd. Finally we study the discrete case for our approximation problem.