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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…
Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference
Zai Yang, Lihua Xie, Cishen Zhang
Direction of arrival (DOA) estimation is a classical problem in signal processing with many practical applications. Its research has recently been advanced owing to the development…
Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP)
Arian Maleki, Laura Anitori, Zai Yang +1
Recovering a sparse signal from an undersampled set of random linear measurements is the main problem of interest in compressed sensing. In this paper, we consider the case where b…