462 citations · 1.7k across the 50 of their papers we have counts for
6 papers · 1 filter
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…
l_0 Norm Constraint LMS Algorithm for Sparse System Identification
Yuantao Gu, Jian Jin, Shunliang Mei
In order to improve the performance of Least Mean Square (LMS) based system identification of sparse systems, a new adaptive algorithm is proposed which utilizes the sparsity prope…
A stochastic gradient approach on compressive sensing signal reconstruction based on adaptive filtering framework
Jian Jin, Yuantao Gu, Shunliang Mei
Based on the methodological similarity between sparse signal reconstruction and system identification, a new approach for sparse signal reconstruction in compressive sensing (CS) i…
A Robust Zero-point Attraction LMS Algorithm on Near Sparse System Identification
Jian Jin, Qing Qu, Yuantao Gu
The newly proposed norm constraint zero-point attraction Least Mean Square algorithm (ZA-LMS) demonstrates excellent performance on exact sparse system identification. Howeve…
Zero-point attracting projection algorithm for sequential compressive sensing
Yang You, Jian Jin, Wei Duan +3
Sequential Compressive Sensing, which may be widely used in sensing devices, is a popular topic of recent research. This paper proposes an online recovery algorithm for sparse appr…
Robustness of Sparse Recovery via -minimization: A Topological Viewpoint
Jingbo Liu, Jian Jin, Yuantao Gu
A recent trend in compressed sensing is to consider non-convex optimization techniques for sparse recovery. The important case of -minimization has become of particular interest…