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Related papers: Continuous Donoho-Elad Spark Uncertainty Principle

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We consider sparse representations of signals from redundant dictionaries which are unions of several orthonormal bases. The spark introduced by Donoho and Elad plays an important role in sparse representations. However, numerical…

Information Theory · Computer Science 2021-09-17 Yi Shen , Chenyun Yu , Yuan Shen , Song Li

The problem of sparse representation has significant applications in signal processing. The spark of a dictionary plays a crucial role in the study of sparse representation. Donoho and Elad initially explored the spark, and they provided a…

Combinatorics · Mathematics 2024-01-30 Tao Zhang , Gennian Ge

Breakthrough Sparsity Theorem, derived independently by Donoho and Elad \textit{[Proc. Natl. Acad. Sci. USA, 2003]}, Gribonval and Nielsen \textit{[IEEE Trans. Inform. Theory, 2003]} and Fuchs \textit{[IEEE Trans. Inform. Theory, 2004]}…

Functional Analysis · Mathematics 2025-08-04 K. Mahesh Krishna

The aim of this paper is to establish a few uncertainty principles for the Fourier and the short-time Fourier transforms. Also, we discuss an analogue of Donoho--Stark uncertainty principle and provide some estimates for the size of the…

Functional Analysis · Mathematics 2021-11-30 Anirudha Poria

Celebrated breakthrough sparsity theorem obtained independently by Donoho and Elad \textit{[Proc. Natl. Acad. Sci. USA, 2003]} and Gribonval and Nielsen \textit{[IEEE Trans. Inform. Theory, 2003]} and Fuchs \textit{[IEEE Trans. Inform.…

Functional Analysis · Mathematics 2025-10-14 K. Mahesh Krishna

Spark plays a great role in studying uniqueness of sparse solutions of the underdetermined linear equations. In this article, we derive a new lower bound of spark. As an application, we obtain a new criterion for the uniqueness of sparse…

Computational Complexity · Computer Science 2012-10-19 Wajeb Gharibi

Let $(\Omega, \mu)$, $(\Delta, \nu)$ be measure spaces and $p=1$ or $p=\infty$. Let $(\{f_\alpha\}_{\alpha\in \Omega}, \{\tau_\alpha\}_{\alpha\in \Omega})$ and $(\{g_\beta\}_{\beta\in \Delta}, \{\omega_\beta\}_{\beta\in \Delta})$ be…

Functional Analysis · Mathematics 2023-12-04 K. Mahesh Krishna

We present some forms of uncertainty principle which involve in a new way localization operators, the concept of $\varepsilon$-concentration and the standard deviation of $L^2$ functions. We show how our results improve the classical…

Functional Analysis · Mathematics 2015-10-12 Paolo Boggiatto , Evanthia Carypis , Alessandro Oliaro

We show that one of the two important uncertainty principles derived by Maccone and Pati \textit{[Phys. Rev. Lett., 2014]} can be derived for arbitrary maps defined on subsets of $\mathcal{L}^p$ spaces for $1< p<\infty$. Our main tool is…

Functional Analysis · Mathematics 2024-02-14 K. Mahesh Krishna

We show how a number of well-known uncertainty principles for the Fourier transform, such as the Heisenberg uncertainty principle, the Donoho--Stark uncertainty principle, and Meshulam's non-abelian uncertainty principle, have little to do…

Functional Analysis · Mathematics 2020-09-14 Avi Wigderson , Yuval Wigderson

In this paper we revisit under-determined linear systems of equations with sparse solutions. As is well known, these systems are among core mathematical problems of a very popular compressed sensing field. The popularity of the field as…

Information Theory · Computer Science 2013-06-18 Mihailo Stojnic

Let $(\{f_j\}_{j=1}^n, \{\tau_j\}_{j=1}^n)$ and $(\{g_k\}_{k=1}^m, \{\omega_k\}_{k=1}^m)$ be p-Schauder frames for a finite dimensional Banach space $\mathcal{X}$. Then for every $x \in \mathcal{X}\setminus\{0\}$, we show that \begin{align}…

Functional Analysis · Mathematics 2026-03-31 K. Mahesh Krishna

We develop new discrete uncertainty principles in terms of numerical sparsity, which is a continuous proxy for the 0-norm. Unlike traditional sparsity, the continuity of numerical sparsity naturally accommodates functions which are nearly…

Information Theory · Computer Science 2017-05-26 Afonso S. Bandeira , Megan E. Lewis , Dustin G. Mixon

In an incoherent dictionary, most signals that admit a sparse representation admit a unique sparse representation. In other words, there is no way to express the signal without using strictly more atoms. This work demonstrates that sparse…

Information Theory · Computer Science 2016-11-18 Joel A. Tropp

This chapter provides a principled introduction to uncertainty relations underlying sparse signal recovery. We start with the seminal work by Donoho and Stark, 1989, which defines uncertainty relations as upper bounds on the operator norm…

Information Theory · Computer Science 2020-03-27 Erwin Riegler , Helmut Bölcskei

Donoho and Stark have shown that a precise deterministic recovery of missing information contained in a time interval shorter than the time-frequency uncertainty limit is possible. We analyze this signal recovery mechanism from a physics…

Quantum Physics · Physics 2015-06-11 Kazuo Fujikawa , Mo-Lin Ge , Yu-Long Liu , Qing Zhao

We present a flexible framework for uncertainty principles in spectral graph theory. In this framework, general filter functions modeling the spatial and spectral localization of a graph signal can be incorporated. It merges several…

Signal Processing · Electrical Eng. & Systems 2019-09-25 Wolfgang Erb

In this paper, we study forms of the uncertainty principle suggested by problems in control theory. We obtain a version of the classical Paneah-Logvinenko-Sereda theorem for the annulus. More precisely, we show that a function with spectrum…

Classical Analysis and ODEs · Mathematics 2021-11-23 Walton Green , Benjamin Jaye , Mishko Mitkovski

The present work aims to search for an implementation of a new symmetry in the space-time by introducing the idea of an invariant minimum speed scale ($V$). Such a lowest limit $V$, being unattainable by the particles, represents a…

General Relativity and Quantum Cosmology · Physics 2017-11-27 Cláudio Nassif

Radar SLAM is robust in challenging conditions, such as fog, dust, and smoke, but suffers from the sparsity and noisiness of radar sensing, including speckle noise and multipath effects. This study provides a performance-enhanced radar SLAM…

Robotics · Computer Science 2025-01-03 Yang Xu , Qiucan Huang , Shaojie Shen , Huan Yin
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