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20112019
most citedOff-grid Direction of Arrival Estimation Using Sparse Bayesian Inference

977 citations · 1.5k across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2019★ 6 cited

Fast Single Image Dehazing via Multilevel Wavelet Transform based Optimization

Jiaxi He, Frank Z. Xing, Ran Yang +1

The quality of images captured in outdoor environments can be affected by poor weather conditions such as fog, dust, and atmospheric scattering of other particles. This problem can…

stat.ML2014

Iterative Bayesian Reconstruction of Non-IID Block-Sparse Signals

Mehdi Korki, Jingxin Zhang, Cishen Zhang +1

This paper presents a novel Block Iterative Bayesian Algorithm (Block-IBA) for reconstructing block-sparse signals with unknown block structures. Unlike the existing algorithms for…

physics.med-ph2014

Parallel MRI Reconstruction by Convex Optimization

Cishen Zhang, Ifat-Al Baqee

In parallel magnetic resonance imaging (pMRI), to find a joint solution for the image and coil sensitivity functions is a nonlinear and nonconvex problem. A class of algorithms rec…

cs.IT2013★ 237 cited

A discretization-free sparse and parametric approach for linear array signal processing

Zai Yang, Lihua Xie, Cishen Zhang

Direction of arrival (DOA) estimation in array processing using uniform/sparse linear arrays is concerned in this paper. While sparse methods via approximate parameter discretizati…

physics.med-ph2013

A Convex Optimization Approach to pMRI Reconstruction

Cishen Zhang, Ifat Al Baqee

In parallel magnetic resonance imaging (pMRI) reconstruction without using estimation of coil sensitivity functions, one group of algorithms reconstruct sensitivity encoded images…

physics.comp-ph2013★ 23 cited

Robust Compressive Phase Retrieval via L1 Minimization With Application to Image Reconstruction

Zai Yang, Cishen Zhang, Lihua Xie

Phase retrieval refers to a classical nonconvex problem of recovering a signal from its Fourier magnitude measurements. Inspired by the compressed sensing technique, signal sparsit…