66 citations · 67 across the 9 of their papers we have counts for
9 papers
Splitting Alternating Algorithms for Sparse Solutions of Linear Systems with Concatenated Orthogonal Matrices
Yun-Bin Zhao, Zhong-Feng Sun
A class of splitting alternating algorithms is proposed for finding the sparse solution of linear systems with concatenated orthogonal matrices. Depending on the number of matrices…
Dynamic Thresholding Algorithm with Memory for Linear Inverse Problems
Zhong-Feng Sun, Yun-Bin Zhao, Jin-Chuan Zhou +1
The relaxed optimal -thresholding pursuit (ROTP) is a recent algorithm for linear inverse problems. This algorithm is based on the optimal -thresholding technique which perfo…
Heavy-ball-based optimal thresholding algorithms for sparse linear inverse problems
Zhong-Feng Sun, Jin-Chuan Zhou, Yun-Bin Zhao
Linear inverse problems arise in diverse engineering fields especially in signal and image reconstruction. The development of computational methods for linear inverse problems with…
Natural Thresholding Algorithms for Signal Recovery with Sparsity
Yun-Bin Zhao, Zhi-Quan Luo
The algorithms based on the technique of optimal -thresholding (OT) were recently proposed for signal recovery, and they are very different from the traditional family of hard t…
Heavy-Ball-Based Hard Thresholding Algorithms for Sparse Signal Recovery
Zhong-Feng Sun, Jin-Chuan Zhou, Yun-Bin Zhao +1
The hard thresholding technique plays a vital role in the development of algorithms for sparse signal recovery. By merging this technique and heavy-ball acceleration method which i…
Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction
Yun-Bin Zhao, Zhi-Quan Luo
The orthogonal matching pursuit (OMP) is one of the mainstream algorithms for sparse data reconstruction or approximation. It acts as a driving force for the development of several…
Partial Gradient Optimal Thresholding Algorithms for a Class of Sparse Optimization Problems
Nan Meng, Yun-Bin Zhao, Michal Kocvara
The optimization problems with a sparsity constraint is a class of important global optimization problems. A typical type of thresholding algorithms for solving such a problem adop…
Newton-Type Optimal Thresholding Algorithms for Sparse Optimization Problems
Nan Meng, Yun-Bin Zhao
Sparse signals can be possibly reconstructed by an algorithm which merges a traditional nonlinear optimization method and a certain thresholding technique. Different from existing…
RSP-Based Analysis for Sparsest and Least -Norm Solutions to Underdetermined Linear Systems
Yunbin Zhao
Recently, the worse-case analysis, probabilistic analysis and empirical justification have been employed to address the fundamental question: When does -minimization find t…