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RNN for Perturbed Manipulability Optimization of Manipulators Based on a Distributed Scheme: A Game-Theoretic Perspective 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5116-5126
作者:  Zhang, Jiazheng;  Jin, Long;  Cheng, Long
收藏  |  浏览/下载：260/0  |  提交时间：2021/03/02
Optimization  Neural networks  Task analysis  Nash equilibrium  Manipulator dynamics  Distributed control  game theory  manipulability optimization  neural network  redundancy resolution  
SRSC: Selective, Robust, and Supervised Constrained Feature Representation for Image Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4290-4302
作者:  Xie, Guo-Sen;  Zhang, Zheng;  Liu, Li;  Zhu, Fan;  Zhang, Xu-Yao;  Shao, Ling;  Li, Xuelong
收藏  |  浏览/下载：210/0  |  提交时间：2021/01/07
Training  Task analysis  Learning systems  Computational modeling  Optimization  Support vector machines  Principal component analysis  Feature learning  feature selection  least squares  subspace learning  
Self-Paced Balance Learning for Clinical Skin Disease Recognition 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 8, 页码: 2832-2846
作者:  Yang, Jufeng;  Wu, Xiaoping;  Liang, Jie;  Sun, Xiaoxiao;  Cheng, Ming-Ming;  Rosin, Paul L.;  Wang, Liang
收藏  |  浏览/下载：227/0  |  提交时间：2020/09/07
Diseases  Skin  Complexity theory  Training  Task analysis  Image recognition  Learning systems  Class imbalance  clinical skin disease recognition  complexity level  self-paced balance learning (SPBL)  
The Strength of Nesterov's Extrapolation in the Individual Convergence of Nonsmooth Optimization 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 7, 页码: 2557-2568
作者:  Tao, Wei;  Pan, Zhisong;  Wu, Gaowei;  Tao, Qing
收藏  |  浏览/下载：226/0  |  提交时间：2020/08/03
Convergence  Extrapolation  Optimization  Acceleration  Machine learning  Task analysis  Machine learning algorithms  Individual convergence  machine learning  Nesterov's extrapolation  nonsmooth optimization  sparsity  
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:  Li, Haoran;  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(4274Kb)  |  收藏  |  浏览/下载：369/114  |  提交时间：2020/08/03
Robot sensing systems  Navigation  Entropy  Neural networks  Task analysis  Planning  Automatic exploration  deep reinforcement learning (DRL)  optimal decision  partial observation