2 citations · 3 across the 7 of their papers we have counts for
7 papers
Unsupervised Classification for Polarimetric SAR Data Using Variational Bayesian Wishart Mixture Model with Inverse Gamma-Gamma Prior
Shijie Ren, Feng Zhou, Changlong Wang
Although various clustering methods have been successfully applied to polarimetric synthetic aperture radar (PolSAR) image clustering tasks, most of the available approaches fail t…
Off-grid Multi-Source Passive Localization Using a Moving Array
Dan Bao, Changlong Wang, Jingjing Cai
A novel direct passive localization technique through a single moving array is proposed in this paper using the sparse representation of the array covariance matrix in spatial doma…
The unified theoretical frame of logarithmic alternative model for sparse information recovery and its application in multiple source location problem by TDOA
Wang Changlong, Zhou Feng, Wang Weichao +1
In sparse information recovery, the core problem is to solve the -minimization which is NP-hard. On one hand, in order to recover the original sparse solution, there are a lot…
A non-convex approach to low-rank and sparse matrix decomposition
Angang Cui, Meng Wen, Haiyang Li +1
In this paper, we develop a nonconvex approach to the problem of low-rank and sparse matrix decomposition. In our nonconvex method, we replace the rank function and the -nor…
Exact sparse reconstruction form Vandermonde matrices
Changlong Wang, Feng Zhou
As a conclusion in classical linear algebra, an underdetermined linear equations usually have an infinite number of solutions. The sparest one among these solutions is significant…
Analysis of equivalence relation in joint sparse recovery
Changlong Wang, Jigen Peng
The joint sparse recovery problem is a generalization of the single measurement vector problem which is widely studied in Compressed Sensing and it aims to recovery a set of jointl…
When is P such that l_0-minimization Equals to l_p-minimization
Changlong Wang, Shigang Yue, Jigen Peng
In this paper, we present an analysis expression of p(A,b) such that the unique solution to l_0-minimization also can be the unique solution to l_p-minimization for any 0<p<p(A,b).…