71 citations · 81 across the 13 of their papers we have counts for
13 papers
Performance analysis of tail-minimization and the linear rate of convergence of a proximal algorithm for sparse signal recovery
Meng Huang, Shidong Li
Recovery error bounds of tail-minimization and the rate of convergence of an efficient proximal alternating algorithm for sparse signal recovery are considered in this article. Tai…
Orthogonal subspace based fast iterative thresholding algorithms for joint sparsity recovery
Ningning Han, Shidong Li, Jian Lu
Sparse signal recoveries from multiple measurement vectors (MMV) with joint sparsity property have many applications in signal, image, and video processing. The problem becomes muc…
Efficient iterative thresholding algorithms with functional feedbacks and convergence analysis
Ningning Han, Shidong Li, Zhanjie Song
An accelerated class of adaptive scheme of iterative thresholding algorithms is studied analytically and empirically. They are based on the feedback mechanism of the null space tun…
The convergence guarantee of the iterative thresholding algorithm with suboptimal feedbacks for large systems
Zhanjie Song, Shidong Li, Ningning Han
Thresholding based iterative algorithms have the trade-off between effectiveness and optimality. Some are effective but involving sub-matrix inversions in every step of iterations.…
The finite steps of convergence of the fast thresholding algorithms with feedbacks
Ningning Han, Shidong Li, Zhanjie Song +1
Iterative algorithms based on thresholding, feedback and null space tuning (NST+HT+FB) for sparse signal recovery are exceedingly effective and fast, particularly for large scale p…
Spark Level Sparsity and the Tail Minimization
Chun-Kit Lai, Shidong Li, Daniel Mondo
Solving compressed sensing problems relies on the properties of sparse signals. It is commonly assumed that the sparsity s needs to be less than one half of the spark of the sensin…