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RNN for Repetitive Motion Generation of Redundant Robot Manipulators: An Orthogonal Projection-Based Scheme 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 2, 页码: 615-628
作者:  Xie, Zhengtai;  Jin, Long;  Luo, Xin;  Sun, Zhongbo;  Liu, Mei
收藏  |  浏览/下载:49/0  |  提交时间:2022/08/22
Manipulators  Kinematics  Recurrent neural networks  Task analysis  Redundancy  Error elimination  gradient descent method  orthogonal projection method  recurrent neural network (RNN)  redundant manipulators  repetitive motion generation (RMG)  
Distributed Competition of Multi-Robot Coordination Under Variable and Switching Topologies 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 页码: 12
作者:  Jin, Long;  Qi, Yimeng;  Luo, Xin;  Li, Shuai;  Shang, Mingsheng
收藏  |  浏览/下载:58/0  |  提交时间:2022/08/22
Robot kinematics  Robots  Topology  Multi-robot systems  Heuristic algorithms  Task analysis  Collaboration  Multi-robot coordination  winner-take-all  gradient neural network  distributed control  
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng
收藏  |  浏览/下载:122/0  |  提交时间:2020/08/24
Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system  
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 卷号: 13, 期号: 6, 页码: 3098-3107
作者:  Luo, Xin;  Sun, Jianpei;  Wang, Zidong;  Li, Shuai;  Shang, Mingsheng
Adobe PDF(803Kb)  |  收藏  |  浏览/下载:426/0  |  提交时间:2018/03/05
Big data application  high-dimensional, and sparse (SHiDS) matrix  nonnegative latent factor (NLF) model  symmetry  undirected HiDS network  
Highly Efficient Framework for Predicting Interactions Between Proteins 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 3, 页码: 731-743
作者:  You, Zhu-Hong;  Zhou, MengChu;  Luo, Xin;  Li, Shuai
Adobe PDF(1407Kb)  |  收藏  |  浏览/下载:218/0  |  提交时间:2018/03/15
Big data  feature extraction  kernel extreme learning machine (K-ELM)  low-rank approximation (LRA)  protein-protein interactions (PPIs)  support vector machine (SVM)