69 citations · 119 across the 13 of their papers we have counts for
6 papers · 1 filter
Solving Quadratic Systems with Full-Rank Matrices Using Sparse or Generative Priors
Junren Chen, Michael K. Ng, Zhaoqiang Liu
The problem of recovering a signal from a quadratic system with full-rank ma…
Bayesian Massive MIMO Channel Estimation with Parameter Estimation Using Low-Resolution ADCs
Shuai Huang, Deqiang Qiu, Trac D. Tran
In order to reduce hardware complexity and power consumption, massive multiple-input multiple-output (MIMO) systems employ low-resolution analog-to-digital converters (ADCs) to acq…
1-Bit Compressive Sensing via Approximate Message Passing with Built-in Parameter Estimation
Shuai Huang, Trac D. Tran
1-bit compressive sensing aims to recover sparse signals from quantized 1-bit measurements. Designing efficient approaches that could handle noisy 1-bit measurements is important i…
Solving Complex Quadratic Systems with Full-Rank Random Matrices
Shuai Huang, Sidharth Gupta, Ivan Dokmanić
We tackle the problem of recovering a complex signal from quadratic measurements of the form , where…
Sparse Signal Recovery via Generalized Entropy Functions Minimization
Shuai Huang, Trac D. Tran
Compressive sensing relies on the sparse prior imposed on the signal of interest to solve the ill-posed recovery problem in an under-determined linear system. The objective functio…
Sparse Signal Recovery using Generalized Approximate Message Passing with Built-in Parameter Estimation
Shuai Huang, Trac D. Tran
The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Comp…