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Given a matrix $A$ with $n$ rows, a number $k<n$, and $0<\delta < 1$, $A$ is $(k,\delta)$-RIP (Restricted Isometry Property) if, for any vector $x \in \mathbb{R}^n$, with at most $k$ non-zero co-ordinates, $$(1-\delta) \|x\|_2 \leq \|A…

Computational Complexity · Computer Science 2014-06-24 Abhiram Natarajan , Yi Wu

Recovery of the initial state of a high-dimensional system can require a large number of measurements. In this paper, we explain how this burden can be significantly reduced when randomized measurement operators are employed. Our work…

Systems and Control · Computer Science 2013-07-17 Borhan M. Sanandaji , Michael B. Wakin , Tyrone L. Vincent

A matrix $A \in \mathbb{C}^{q \times N}$ satisfies the restricted isometry property of order $k$ with constant $\varepsilon$ if it preserves the $\ell_2$ norm of all $k$-sparse vectors up to a factor of $1\pm \varepsilon$. We prove that a…

Data Structures and Algorithms · Computer Science 2015-10-14 Ishay Haviv , Oded Regev

The expicit restricted isometry property (RIP) measurement matrices are needed in practical application of compressed sensing in signal processing. RIP matrices from Reed-Solomon codes, BCH codes, orthogonal codes, expander graphs have been…

Information Theory · Computer Science 2015-06-15 Liqing Xu , Hao Chen

In this paper, we consider the extensively studied problem of computing a $k$-sparse approximation to the $d$-dimensional Fourier transform of a length $n$ signal. Our algorithm uses $O(k \log k \log n)$ samples, is dimension-free, operates…

Data Structures and Algorithms · Computer Science 2019-09-26 Vasileios Nakos , Zhao Song , Zhengyu Wang

We study the restricted isometry property of a matrix that is built from the discrete Fourier transform matrix by collecting rows indexed by quadratic residues. We find an $\epsilon>0$ such that, conditioned on a folklore conjecture in…

Functional Analysis · Mathematics 2014-10-24 Afonso S. Bandeira , Dustin G. Mixon , Joel Moreira

In this paper, we study the restricted isometry property of partial random circulant matrices. For a bounded subgaussian generator with independent entries, we prove that the partial random circulant matrices satisfy $s$-order RIP with high…

Information Theory · Computer Science 2018-08-23 Meng Huang , Yuxuan Pang , Zhiqiang Xu

A matrix is said to possess the Restricted Isometry Property (RIP) if it acts as an approximate isometry when restricted to sparse vectors. Previous work has shown it to be NP-hard to determine whether a matrix possess this property, but…

Computational Complexity · Computer Science 2018-07-04 Jonathan Weed

Matrices with the restricted isometry property (RIP) are of particular interest in compressed sensing. To date, the best known RIP matrices are constructed using random processes, while explicit constructions are notorious for performing at…

Functional Analysis · Mathematics 2014-03-17 Dustin G. Mixon

The restricted isometry property (RIP) is a universal tool for data recovery. We explore the implication of the RIP in the framework of generalized sparsity and group measurements introduced in the Part I paper. It turns out that for a…

Machine Learning · Statistics 2017-07-03 Marius Junge , Kiryung Lee

Some consequences of the Restricted Isometry Property (RIP) of matrices have been applied to develop a greedy algorithm called "ROMP" (Regularized Orthogonal Matching Pursuit) to recover sparse signals and to approximate non-sparse ones.…

Information Theory · Computer Science 2013-05-31 Eugenio Hernández , Daniel Vera

We construct orthogonal arrays OA$_{\lambda} (k,n)$ (of strength two) having a row that is repeated $m$ times, where $m$ is as large as possible. In particular, we consider OAs where the ratio $m / \lambda$ is as large as possible; these…

Combinatorics · Mathematics 2018-12-14 Charles J. Colbourn , Douglas R. Stinson , Shannon Veitch

Recently, many works have focused on the characterization of non-linear dimensionality reduction methods obtained by quantizing linear embeddings, e.g., to reach fast processing time, efficient data compression procedures, novel…

Information Theory · Computer Science 2016-12-30 Laurent Jacques , Valerio Cambareri

Structures play a significant role in the field of signal processing. As a representative of structural data, low rank matrix along with its restricted isometry property (RIP) has been an important research topic in compressive signal…

Information Theory · Computer Science 2015-06-23 Xinyue Shen , Yuantao Gu

The simulations indicate that the existing hard thresholding technique independent of the residual function may cause a dramatic increase or numerical oscillation of the residual. This inherit drawback of the hard thresholding renders the…

Information Theory · Computer Science 2019-09-04 Yun-Bin Zhao

Hierarchically sparse signals and Kronecker product structured measurements arise naturally in a variety of applications. The simplest example of a hierarchical sparsity structure is two-level $(s,\sigma)$-hierarchical sparsity which…

Information Theory · Computer Science 2018-02-01 I. Roth , A. Flinth , R. Kueng , J. Eisert , G. Wunder

In the field of compressed sensing, a key problem remains open: to explicitly construct matrices with the restricted isometry property (RIP) whose performance rivals those generated using random matrix theory. In short, RIP involves…

Functional Analysis · Mathematics 2012-10-02 Matthew Fickus , John Jasper , Dustin G. Mixon , Jesse Peterson

This paper establishes a sharp condition on the restricted isometry property (RIP) for both the sparse signal recovery and low-rank matrix recovery. It is shown that if the measurement matrix $A$ satisfies the RIP condition…

Information Theory · Computer Science 2013-02-07 T. Tony Cai , Anru Zhang

We prove that quaternion Gaussian random matrices satisfy the restricted isometry property (RIP) with overwhelming probability. We also explain why the restricted isometry random variables (RIV) approach is not appropriate for drawing…

Probability · Mathematics 2017-05-01 Agnieszka Badeńska , Łukasz Błaszczyk

Orthogonal Matching Pursuit (OMP) is the canonical greedy algorithm for sparse approximation. In this paper we demonstrate that the restricted isometry property (RIP) can be used for a very straightforward analysis of OMP. Our main…

Numerical Analysis · Mathematics 2009-09-02 Mark A. Davenport , Michael B. Wakin