W
Wenli Xu
Researcher at Tsinghua University
Publications - 144
Citations - 4824
Wenli Xu is an academic researcher from Tsinghua University. The author has contributed to research in topics: Video tracking & Sparse approximation. The author has an hindex of 30, co-authored 143 publications receiving 4458 citations.
Papers
More filters
Journal ArticleDOI
RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images
TL;DR: This paper reduces this extremely challenging optimization problem to a sequence of convex programs that minimize the sum of l1-norm and nuclear norm of the two component matrices, which can be efficiently solved by scalable convex optimization techniques.
Proceedings ArticleDOI
RASL: Robust alignment by sparse and low-rank decomposition for linearly correlated images
TL;DR: This paper reduces this extremely challenging optimization problem to a sequence of convex programs that minimize the sum of ℓ1-norm and nuclear norm of the two component matrices, which can be efficiently solved by scalable convex optimization techniques with guaranteed fast convergence.
Journal ArticleDOI
Adaptive Sliding-Mode Guidance of a Homing Missile
D.H. Zhou,Chundi Mu,Wenli Xu +2 more
TL;DR: In this article, an adaptive reaching law of sliding mode for a linear time-varying system is presented and used to derive an adaptive sliding-mode guidance law, which is robust against disturbances and parameter perturbations.
Journal ArticleDOI
A novel approach to fuzzy rough sets based on a fuzzy covering
TL;DR: The new model for fuzzy rough sets is based on the concepts of both fuzzy covering and binary fuzzy logical operators (fuzzy conjunction and fuzzy implication) and a link between the generalized fuzzy rough approximation operators and fundamental morphological operators is presented in a translation-invariant additive group.
Journal ArticleDOI
A comparative study on sufficient conditions for Takagi-Sugeno fuzzy systems as universal approximators
Ke Zeng,Nai-Yao Zhang,Wenli Xu +2 more
TL;DR: New sufficient conditions for simplified fuzzy systems and linear TS fuzzy systems as universal approximators are given, respectively and a comparative study on existing sufficient conditions is carried out with numeric examples.