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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：301/0  |  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：256/0  |  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