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In Compressive Sensing, the Restricted Isometry Property (RIP) ensures that robust recovery of sparse vectors is possible from noisy, undersampled measurements via computationally tractable algorithms. It is by now well-known that Gaussian…

信息论 · 计算机科学 2014-02-17 Armin Eftekhari , Han Lun Yap , Christopher J. Rozell , Michael B. Wakin

The restricted isometry property (RIP) is a well-known matrix condition that provides state-of-the-art reconstruction guarantees for compressed sensing. While random matrices are known to satisfy this property with high probability,…

泛函分析 · 数学 2012-02-24 Afonso S. Bandeira , Matthew Fickus , Dustin G. Mixon , Percy Wong

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…

信息论 · 计算机科学 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…

计算复杂性 · 计算机科学 2018-07-04 Jonathan Weed

Matrices satisfying the Restricted Isometry Property (RIP) play an important role in the areas of compressed sensing and statistical learning. RIP matrices with optimal parameters are mainly obtained via probabilistic arguments, as explicit…

机器学习 · 计算机科学 2019-11-01 Shiva Prasad Kasiviswanathan , Mark Rudelson

The restricted isometry property (RIP) is essential for the linear map to guarantee the successful recovery of low-rank matrices. The existing works show that the linear map generated by the measurement matrices with independent and…

信息论 · 计算机科学 2024-05-08 Wei Zhang , Zhenni Wang

It is now well known that sparse or compressible vectors can be stably recovered from their low-dimensional projection, provided the projection matrix satisfies a Restricted Isometry Property (RIP). We establish new implications of the RIP…

泛函分析 · 数学 2012-11-09 Rémi Gribonval , Morten Nielsen

A matrix $\Phi \in \mathbb{R}^{Q \times N}$ satisfies the restricted isometry property if $\|\Phi x\|_2^2$ is approximately equal to $\|x\|_2^2$ for all $k$-sparse vectors $x$. We give a construction of RIP matrices with the optimal $Q =…

信息论 · 计算机科学 2024-12-19 Shravas Rao

The study of the restricted isometry property (RIP) of corrupted random matrices is particularly important in the field of compressed sensing (CS) with corruptions. If a matrix still satisfies the RIP after that a certain portion of rows…

概率论 · 数学 2019-03-22 Ran Lu

We formulate a generalization of the Restricted Isometry Property (RIP) referred to as the Restricted Quasiconvexity Isometry Property (RQIP) for alpha stable random projections with $0<\alpha<1$. A lower bound on the number of rows for…

概率论 · 数学 2025-07-04 Sunder Ram Krishnan

This paper is concerned with an important matrix condition in compressed sensing known as the restricted isometry property (RIP). We demonstrate that testing whether a matrix satisfies RIP is NP-hard. As a consequence of our result, it is…

泛函分析 · 数学 2017-10-03 Afonso S. Bandeira , Edgar Dobriban , Dustin G. Mixon , William F. Sawin

In this paper, we prove that the Paley graph conjecture implies that the Paley matrix has restricted isometry property (RIP) beating the square-root bottleneck for the sparsity level. Moreover, we show that the RIP of the Paley matrix…

组合数学 · 数学 2020-11-09 Shohei Satake

Restricted Isometry Property (RIP) is of fundamental importance in the theory of compressed sensing and forms the base of many exact and robust recovery guarantees in this field. A quantitative description of RIP involves bounding the…

信息论 · 计算机科学 2020-07-15 Gen Li , Xingyu Xu , Yuantao Gu

Matrices $\Phi\in\R^{n\times p}$ satisfying the Restricted Isometry Property (RIP) are an important ingredient of the compressive sensing methods. While it is known that random matrices satisfy the RIP with high probability even for…

概率论 · 数学 2018-11-19 David Gamarnik

Dimension reduction plays an essential role when decreasing the complexity of solving large-scale problems. The well-known Johnson-Lindenstrauss (JL) Lemma and Restricted Isometry Property (RIP) admit the use of random projection to reduce…

信息论 · 计算机科学 2018-03-14 Gen Li , Yuantao Gu

In [8] the author of this paper continued the research on the complex-valued discrete random variables $X_l(m,N)$ ($0\le l\le N-1$, $1\le M\le N)$ recently introduced and studied in [24]. Here we extend our results by considering $X_l(m,N)$…

概率论 · 数学 2018-03-14 Romeo Meštrović

In this paper we study the robustness properties of dimensionality reduction with Gaussian random matrices having arbitrarily erased rows. We first study the robustness property against erasure for the almost norm preservation property of…

信息论 · 计算机科学 2015-01-09 Bin Han , Zhiqiang Xu

We consider a random matrix whose entries are independent Gaussian variables taking values in the field of quaternions with variance $1/n$. Using logarithmic potential theory, we prove the almost sure convergence, as the dimension $n$ goes…

概率论 · 数学 2011-09-05 Florent Benaych-Georges , Francois Chapon

In previous work, theoretical analysis based on the tensor Restricted Isometry Property (t-RIP) established the robust recovery guarantees of a low-tubal-rank tensor. The obtained sufficient conditions depend strongly on the assumption that…

机器学习 · 统计学 2019-09-17 Feng Zhang , Wendong Wang , Jingyao Hou , Jianjun Wang , Jianwen Huang

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…

数据结构与算法 · 计算机科学 2015-10-14 Ishay Haviv , Oded Regev
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