88 citations · 116 across the 7 of their papers we have counts for
7 papers
Sparse Recovery with Graph Constraints
Meng Wang, Weiyu Xu, Enrique Mallada +1
Sparse recovery can recover sparse signals from a set of underdetermined linear measurements. Motivated by the need to monitor large-scale networks from a limited number of measure…
Sparse Recovery from Nonlinear Measurements with Applications in Bad Data Detection for Power Networks
Weiyu Xu, Meng Wang, Jianfeng Cai +1
In this paper, we consider the problem of sparse recovery from nonlinear measurements, which has applications in state estimation and bad data detection for power networks. An iter…
Sparse Recovery with Graph Constraints: Fundamental Limits and Measurement Construction
Meng Wang, Weiyu Xu, Enrique Mallada +1
This paper addresses the problem of sparse recovery with graph constraints in the sense that we can take additive measurements over nodes only if they induce a connected subgraph.…
On State Estimation with Bad Data Detection
Weiyu Xu, Meng Wang, Ao Tang
In this paper, we consider the problem of state estimation through observations possibly corrupted with both bad data and additive observation noises. A mixed and …
On the Performance of Sparse Recovery via L_p-minimization (0<=p <=1)
Meng Wang, Weiyu Xu, Ao Tang
It is known that a high-dimensional sparse vector x* in R^n can be recovered from low-dimensional measurements y= A^{m*n} x* (m<n) . In this paper, we investigate the recovering ab…
The Limits of Error Correction with lp Decoding
Meng Wang, Weiyu Xu, Ao Tang
An unknown vector f in R^n can be recovered from corrupted measurements y = Af + e where A^(m*n)(m>n) is the coding matrix if the unknown error vector e is sparse. We investigate t…