中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Online Active Continual Learning for Robotic Lifelong Object Recognition 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 15
作者:  Nie, Xiangli;  Deng, Zhiguang;  He, Mingdong;  Fan, Mingyu;  Tang, Zheng
收藏  |  浏览/下载：124/0  |  提交时间：2023/11/16
Task analysis  Robots  Data models  Object recognition  Learning systems  Training  Heuristic algorithms  Catastrophic forgetting  lifelong object recognition  online active learning (OAL)  online continual learning (OCL)  
Bioinspired Gain-Modulated Recurrent Neural Network for Controlling Musculoskeletal Robot 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 16
作者:  Zhong, Shanlin;  Zhou, Junjie;  Qiao, Hong
收藏  |  浏览/下载：262/0  |  提交时间：2022/01/27
Robots  Modulation  Robot kinematics  Neurons  Brain modeling  Recurrent neural networks  Encoding  Biologically inspired control  gain modulation  motor primitives  musculoskeletal robot  recurrent neural network (RNN)  
Target Tracking Control of a Biomimetic Underwater Vehicle Through Deep Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 12
作者:  Wang, Yu;  Tang, Chong;  Wang, Shuo;  Cheng, Long;  Wang, Rui;  Tan, Min;  Hou, Zengguang
收藏  |  浏览/下载：274/0  |  提交时间：2022/01/27
Reinforcement learning  Target tracking  Robots  Sports  Aerospace electronics  Mobile robots  Underwater vehicles  Biomimetic underwater vehicle (BUV)  reinforcement learning  target tracking control  
Complex-Valued Discrete-Time Neural Dynamics for Perturbed Time-Dependent Complex Quadratic Programming With Applications 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 9, 页码: 3555-3569
作者:  Qi, Yimeng;  Jin, Long;  Wang, Yaonan;  Xiao, Lin;  Zhang, Jiliang
收藏  |  浏览/下载：232/0  |  提交时间：2021/01/07
Computational modeling  Convergence  Mathematical model  Recurrent neural networks  Perturbation methods  Robots  Numerical models  Complex domain  discrete-time neural dynamics (DTND)  quasi-Newton Broyden-Fletcher-Goldfarb-Shanno (BFGS)  quadratic programming (QP)  
Composite Learning Enhanced Robot Impedance Control 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 3, 页码: 1052-1059
作者:  Sun, Tairen;  Peng, Liang;  Cheng, Long;  Hou, Zeng-Guang;  Pan, Yongping
收藏  |  浏览/下载：290/0  |  提交时间：2020/06/02
Impedance  Convergence  Robots  Stability criteria  Uncertainty  Parameter estimation  Adaptive control  composite adaptation  impedance control  learning control  parameter convergence  robot