76 citations · 186 across the 27 of their papers we have counts for
15 papers · 1 filter
CFAR based NOMP for Line Spectral Estimation and Detection
Menghuai Xu, Jiang Zhu, Jun Fang +2
The line spectrum estimation problem is considered in this paper. We propose a CFAR-based Newtonized OMP (NOMP-CFAR) method which can maintain a desired false alarm rate without th…
A Unitary Transform Based Generalized Approximate Message Passing
Jiang Zhu, Xiangming Meng, Xupeng Lei +1
We consider the problem of recovering an unknown signal from general nonlinear measurements obtained through a generalized linear model (GLM), i.e.,…
Joint CFO, Gridless Channel Estimation and Data Detection for Underwater Acoustic OFDM Systems
Lei Wan, Jiang Zhu, En Cheng +1
In this paper, we propose an iterative receiver based on gridless variational Bayesian line spectra estimation (VALSE) named JCCD-VALSE that \emph{j}ointly estimates the \emph{c}ar…
Multidimensional Variational Line Spectra Estimation
Qi Zhang, Jiang Zhu, Ning Zhang +1
The fundamental multidimensional line spectral estimation problem is addressed utilizing the Bayesian methods. Motivated by the recently proposed variational line spectral estimati…
Matrix Completion from Quantized Samples via Generalized Sparse Bayesian Learning
Jiang Zhu, Zhennan Liu, Qi Zhang +2
The recovery of a low rank matrix from a subset of noisy low-precision quantized samples arises in several applications such as collaborative filtering, intelligent recommendation…
Expectation Propagation based Line Spectral Estimation
Jiang Zhu, Xupeng Lei, Mihai Alin-Badiu +1
The fundamental problem of line spectral estimation (LSE) using the expectation propagation (EP) method is studied. Previous approaches estimate the model order sequentially, limit…
Grid-less Variational Bayesian Inference of Line Spectral from Quantized Samples
Jiang Zhu, Qi Zhang, Xiangming Meng
Efficient estimation of line spectral from quantized samples is of significant importance in information theory and signal processing, e.g., channel estimation in energy efficient…
Bilinear Adaptive Generalized Vector Approximate Message Passing
Xiangming Meng, Jiang Zhu
This paper considers the generalized bilinear recovery problem which aims to jointly recover the vector and the matrix from componentwise nonlinear measurem…
Binary Sparse Bayesian Learning Algorithm for One-bit Compressed Sensing
Jiang Zhu, Lin Han, Xiangming Meng +1
In this letter, a binary sparse Bayesian learning (BSBL) algorithm is proposed to slove the one-bit compressed sensing (CS) problem in both single measurement vector (SMV) and mult…
A Two-stage Approach to Estimate CFO and Channel with One-bit ADCs
Jiang Zhu, Hangting Cao, Zhiwei Xu
In this letter, we propose a two-stage approach to estimate the carrier frequency offset (CFO) and channel with one-bit analog-to-digital converters (ADCs). Firstly, a simple metri…
Variational Bayesian Line Spectral Estimation with Multiple Measurement Vectors
Jiang Zhu, Qi Zhang, Peter Gerstoft +2
In this paper, the line spectral estimation (LSE) problem with multiple measurement vectors (MMVs) is studied utilizing the Bayesian methods. Motivated by the recently proposed var…
Multi-snapshot Newtonized Orthogonal Matching Pursuit for Line Spectrum Estimation with Multiple Measurement Vectors
Jiang Zhu, Lin Han, Rick S. Blum +1
In this paper, multi-snapshot Newtonized orthogonal matching pursuit (MNOMP) algorithm is proposed to deal with the line spectrum estimation with multiple measurement vectors (MMVs…
A Unified Bayesian Inference Framework for Generalized Linear Models
Xiangming Meng, Sheng Wu, Jiang Zhu
In this letter, we present a unified Bayesian inference framework for generalized linear models (GLM) which iteratively reduces the GLM problem to a sequence of standard linear mod…
Signal Amplitude Estimation and Detection from Unlabeled Binary Quantized Samples
Guanyu Wang, Jiang Zhu, Rick S. Blum +4
Signal amplitude estimation and detection from unlabeled quantized binary samples are studied, assuming that the order of the time indexes is completely unknown. First, maximum lik…
Maximum Likelihood Estimation from Sign Measurements with Sensing Matrix Perturbation
Jiang Zhu, Xiaohan Wang, Yuantao Gu
The problem of estimating an unknown deterministic parameter vector from sign measurements with a perturbed sensing matrix is studied in this paper. We analyze the best achievable…