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20152022
most citedSignal-Dependent Performance Analysis of Orthogonal Matching Pursuit for Exact Sparse Recovery

39 citations · 39 across the 6 of their papers we have counts for

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cs.IT2022

Sharper Bounds on Four Lattice Constants

Jinming Wen, Xiao-Wen Chang

The Korkine--Zolotareff (KZ) reduction, and its generalisations, are widely used lattice reduction strategies in communications and cryptography. The KZ constant and Schnorr's cons…

cs.IT2021

On the Success Probability of Three Detectors for the Box-Constrained Integer Linear Model

Jinming Wen, Xiao Wen Chang

This paper is concerned with detecting an integer parameter vector inside a box from a linear model that is corrupted with a noise vector following the Gaussian distribution. One o…

cs.IT202039 cited

Signal-Dependent Performance Analysis of Orthogonal Matching Pursuit for Exact Sparse Recovery

Jinming Wen, Rui Zhang, Wei Yu

Exact recovery of -sparse signals from linear measurements , where is a sensing matrix, arises from many applications.…

cs.IT2019

Exact Sparse Signal Recovery via Orthogonal Matching Pursuit with Prior Information

Jinming Wen, Wei Yu

The orthogonal matching pursuit (OMP) algorithm is a commonly used algorithm for recovering -sparse signals $\x\in \mathbb{R}^{n}$ from linear model $\y=\A\x$, where $\A\in \mat…

cs.IT2019

Improved Upper Bounds on the Hermite and KZ Constants

Jinming Wen, Xiao-Wen Chang, Jian Weng

The Korkine-Zolotareff (KZ) reduction is a widely used lattice reduction strategy in communications and cryptography. The Hermite constant, which is a vital constant of lattice, ha…

cs.IT2018

A New Analysis for Support Recovery with Block Orthogonal Matching Pursuit

Haifeng Li, Jinming Wen

Compressed Sensing (CS) is a signal processing technique which can accurately recover sparse signals from linear measurements with far fewer number of measurements than those requi…