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researcher

C. Leung

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.SP2
  • cs.LG1
  • eess.IV1
same name
  • C. Leung — 16 papers
  • C. Leung — 12 papers, h 9
  • C. Leung — 7 papers, h 14
  • C. Leung — 6 papers, h 10
  • C. Leung — 5 papers, h 21
  • C. Leung — 4 papers, h 42

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

eess.IV2018

Robust Real-time Ellipse Fitting Based on Lagrange Programming Neural Network and Locally Competitive Algorithm

Hao Wang, Chi-Sing Leung, Hing Cheung So +3

Given a set of 2-dimensional (2-D) scattering points, which are usually obtained from the edge detection process, the aim of ellipse fitting is to construct an elliptic equation th…

eess.SP2018

Robust MIMO Radar Target Localization based on Lagrange Programming Neural Network

Hao Wang, Chi-Sing Leung, Hing Cheung So +3

This paper focuses on target localization in a widely distributed multiple-input-multiple-output (MIMO) radar system. In this system, range measurements, which include the sum of d…

eess.SP2018

ADMM-MCP Framework for Sparse Recovery with Global Convergence

Hao Wang, Zhanglei Shi, Chi-Sing Leung +1

In compressed sensing, the l0-norm minimization of sparse signal reconstruction is NP-hard. Recent work shows that compared with the best convex relaxation (l1-norm), nonconvex pen…

cs.LG2018

l0-norm Based Centers Selection for Training Fault Tolerant RBF Networks and Selecting Centers

Hao Wang, Chi-Sing Leung, Hing Cheung So +2

The aim of this paper is to train an RBF neural network and select centers under concurrent faults. It is well known that fault tolerance is a very attractive property for neural n…

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