977 citations · 1.5k across the 13 of their papers we have counts for
6 papers · 1 filter
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…
Bayesian compressed sensing with new sparsity-inducing prior
Zai Yang, Lihua Xie, Cishen Zhang
Sparse Bayesian learning (SBL) is a popular approach to sparse signal recovery in compressed sensing (CS). In SBL, the signal sparsity information is exploited by assuming a sparsi…
Variational Bayesian algorithm for quantized compressed sensing
Zai Yang, Lihua Xie, Cishen Zhang
Compressed sensing (CS) is on recovery of high dimensional signals from their low dimensional linear measurements under a sparsity prior and digital quantization of the measurement…
Robustly Stable Signal Recovery in Compressed Sensing with Structured Matrix Perturbation
Zai Yang, Cishen Zhang, Lihua Xie
The sparse signal recovery in the standard compressed sensing (CS) problem requires that the sensing matrix be known a priori. Such an ideal assumption may not be met in practical…
On Phase Transition of Compressed Sensing in the Complex Domain
Zai Yang, Cishen Zhang, Lihua Xie
The phase transition is a performance measure of the sparsity-undersampling tradeoff in compressed sensing (CS). This letter reports our first observation and evaluation of an empi…
Orthonormal Expansion l1-Minimization Algorithms for Compressed Sensing
Zai Yang, Cishen Zhang, Jun Deng +1
Compressed sensing aims at reconstructing sparse signals from significantly reduced number of samples, and a popular reconstruction approach is -norm minimization. In this…