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Real-Time Digital Video Stabilization of Bioinspired Robotic Fish Using Estimation-and-Prediction Framework 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2022, 页码: 12
作者:  Meng, Yan;  Wu, Zhengxing;  Zhang, Pengfei;  Wang, Jian;  Yu, Junzhi
Adobe PDF(3860Kb)  |  收藏  |  浏览/下载：335/64  |  提交时间：2022/06/06
Bioinspired robot  digital video stabilization  estimation-and-prediction framework  robotic fish  vision system  
Active Disturbance Rejection Control for a Fluid-Driven Hand Rehabilitation Device 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 卷号: 26, 期号: 2, 页码: 841-853
作者:  Li, Houcheng;  Cheng, Long;  Li, Zhengwei;  Xue, Wenchao
Adobe PDF(3069Kb)  |  收藏  |  浏览/下载：267/39  |  提交时间：2021/06/07
Actuators  Exoskeletons  Performance evaluation  Training  IEEE transactions  Mechatronics  Active disturbance rejection control  extended state observer  extension motion  hand rehabilitation  parameter selection  transient  steady-state performance  
Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation 期刊论文
FRONTIERS IN NEUROROBOTICS, 2020, 卷号: 12, 期号: 无, 页码: 11
作者:  Wang, Jiaxing;  Wang, Weiqun;  Ren, Shixin;  Shi, Weiguo;  Hou, Zeng-Guang
Adobe PDF(2370Kb)  |  收藏  |  浏览/下载：300/69  |  提交时间：2021/01/06
human-in-the-loop optimization  EEG based neural engagement  sEMG based muscle activation  tracking accuracy  neural rehabilitation  
Learning impedance control of robots with enhanced transient and steady-state control performances 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 9, 页码: 13
作者:  Sun, Tairen;  Cheng, Long;  Peng, Liang;  Hou, Zengguang;  Pan, Yongping
收藏  |  浏览/下载：190/0  |  提交时间：2020/09/07
robot  adaptive control  neural network  impedance control  parameter convergence  
A Curiosity-Based Learning Method for Spiking Neural Networks 期刊论文
Frontiers in Computational Neuroscience, 2020, 卷号: 14, 期号: 14, 页码: 7
作者:  Shi, Mengting;  Zhang, Tielin;  Zeng, Yi
Adobe PDF(1349Kb)  |  收藏  |  浏览/下载：375/102  |  提交时间：2020/04/27
Curiosity  Spiking Neural Network  Novelty  Stdp  Voltage-driven Plasticity-centric Snn