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Effective support, Dirac combs, and signal recovery

Published 28 Nov 2024 in math.CA and math.CO | (2411.19195v1)

Abstract: Let $f: {\mathbb Z}Nd \to {\mathbb C}$ be a signal with the Fourier transform $\widehat{f}: \Bbb Z_Nd\to \Bbb C$. A classical result due to Matolcsi and Szucs (\cite{MS73}), and, independently, to Donoho and Stark (\cite{DS89}) states if a subset of frequencies ${{\widehat{f}(m)}}{m \in S}$ of $f$ are unobserved due to noise or other interference, then $f$ can be recovered exactly and uniquely provided that $$ |E| \cdot |S|<\frac{Nd}{2},$$ where $E$ is the support of $f$, i.e., $E={x \in {\mathbb Z}Nd: f(x) \not=0}$. In this paper, we consider signals that are Dirac combs of complexity $\gamma$, meaning they have the form $f(x)=\sum{i=1}{\gamma} a_i 1_{A_i}(x)$, where the sets $A_i \subset {\mathbb Z}_Nd$ are disjoint, $a_i$ are complex numbers, and $\gamma \leq Nd$. We will define the concept of effective support of these signals and show that if $\gamma$ is not too large, a good recovery condition can be obtained by pigeonholing under additional reasonable assumptions on the distribution of values. Our approach produces a non-trivial uncertainty principle and a signal recovery condition in many situations when the support of the function is too large to apply the classical theory.

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