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We propose a class of greedy algorithms for weighted sparse recovery by considering new loss function-based generalizations of Orthogonal Matching Pursuit (OMP). Given a (regularized) loss function, the proposed algorithms alternate the…

Information Theory · Computer Science 2025-02-18 Sina Mohammad-Taheri , Simone Brugiapaglia

New constraints based on practical hardware are introduced in compressive sensing (CS) based rectangular antenna array thinning technique. In a standard CS array sparsity enforcement, antenna elements are considered as ideal point sources…

Signal Processing · Electrical Eng. & Systems 2019-07-23 M. Ali Babar Abbasi , Vincent F. Fusco

We study Sparse Signal Recovery (SSR) methods for multichannel imaging with compressed {forward and backward} operators that preserve reconstruction accuracy. We propose a Compressed Block-Convolutional (C-BC) measurement model based on a…

Image and Video Processing · Electrical Eng. & Systems 2026-02-02 Han Wang , Yhonatan Kvich , Eduardo Pérez , Florian Römer , Yonina C. Eldar

This paper deals with the design of a sensing matrix along with a sparse recovery algorithm by utilizing the probability-based prior information for compressed sensing system. With the knowledge of the probability for each atom of the…

Machine Learning · Computer Science 2019-10-29 Q. Jiang , S. Li , Z. Zhu , H. Bai , X. He , R. C. de Lamare

In this paper we present a new coherence-based performance guarantee for the Orthogonal Matching Pursuit (OMP) algorithm. An upper bound for the probability of correctly identifying the support of a sparse signal with additive white…

Information Theory · Computer Science 2016-10-25 Mohammad Emadi , Ehsan Miandji , Jonas Unger , Ehsan Afshari

We study the problem of recovering the sparsity pattern of block-sparse signals from noise-corrupted measurements. A simple, efficient recovery method, namely, a block-version of the orthogonal matching pursuit (OMP) method, is considered…

Information Theory · Computer Science 2011-09-27 Jun Fang , Hongbin Li

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this letter. Based on a system model that takes into account the effects of synchronization impairments such as…

Information Theory · Computer Science 2013-04-30 Renu Jose , Sooraj K. Ambat , K. V. S. Hari

In this article, we address the problem of reducing the number of required samples for Spherical Near-Field Antenna Measurements (SNF) by using Compressed Sensing (CS). A condition to ensure the numerical performance of sparse recovery…

Information Theory · Computer Science 2023-02-10 Arya Bangun , Cosme Culotta-López

In this paper we define a new coherence index, named the global 2-coherence, of a given dictionary and study its relationship with the traditional mutual coherence and the restricted isometry constant. By exploring this relationship, we…

Information Theory · Computer Science 2014-05-15 Mingrui Yang , Frank de Hoog

Compressive approaches provide a means of effective channel high resolution channel estimates in millimeter wave MIMO systems, despite the use of analog and hybrid architectures. Such estimates can also be used as part of a joint channel…

Signal Processing · Electrical Eng. & Systems 2022-04-08 Joan Palacios , Nuria González-Prelcic , Cristian Rusu

Conventional correlation-based frame synchronization techniques can suffer significant performance degradation over multi-path frequency-selective channels. As a remedy, in this paper we consider joint frame synchronization and channel…

Information Theory · Computer Science 2017-09-06 Ozgur Ozdemir , Ridha Hamila , Naofal Al-Dhahir , Ismail Guvenc

Support recovery of sparse signals from noisy measurements with orthogonal matching pursuit (OMP) has been extensively studied in the literature. In this paper, we show that for any $K$-sparse signal $\x$, if the sensing matrix $\A$…

Information Theory · Computer Science 2018-07-13 JInming Wen , Zhengchun Zhou , Jian Wang , Xiaohu Tang , Qun Mo

This paper considers the problem of designing sparse linear tripole arrays. In such arrays at each antenna location there are three orthogonal dipoles, allowing full measurement of both the horizontal and vertical components of the received…

Information Theory · Computer Science 2017-02-15 Matthew Hawes , Wei Liu , Lyudmila Mihaylova

Sparse signals (i.e., vectors with a small number of non-zero entries) build the foundation of most kernel (or nullspace) results, uncertainty relations, and recovery guarantees in the sparse signal processing and compressive sensing…

Information Theory · Computer Science 2015-07-13 Christoph Studer

Greed is good. However, the tighter you squeeze, the less you have. In this paper, a less greedy algorithm for sparse signal reconstruction in compressive sensing, named orthogonal matching pursuit with thresholding is studied. Using the…

Information Theory · Computer Science 2015-07-03 Mingrui Yang , Frank de Hoog

The simultaneous orthogonal matching pursuit (SOMP) algorithm aims to find the joint support of a set of sparse signals acquired under a multiple measurement vector model. Critically, the analysis of SOMP depends on the maximal inner…

Information Theory · Computer Science 2016-10-14 Jean-François Determe , Jérôme Louveaux , Laurent Jacques , François Horlin

Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding non-convex…

Information Theory · Computer Science 2020-12-03 Yann Traonmilin , Jean-François Aujol , Arhur Leclaire

As an extension of orthogonal matching pursuit (OMP) improving the recovery performance of sparse signals, generalized OMP (gOMP) has recently been studied in the literature. In this paper, we present a new analysis of the gOMP algorithm…

Information Theory · Computer Science 2015-06-15 Jian Wang , Suhyuk Kwon , Ping Li , Byonghyo Shim

Measurement samples are often taken in various monitoring applications. To reduce the sensing cost, it is desirable to achieve better sensing quality while using fewer samples. Compressive Sensing (CS) technique finds its role when the…

Information Theory · Computer Science 2016-11-18 Ying Li , Kun Xie , Xin Wang

In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting inter-symbol interference (ISI)…

Information Theory · Computer Science 2015-04-22 Guan Gui , Li Xu , Lin Shan , Fumiyuki Adachi
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