A Multi-scale Temporal Convolutional Network-based Method for sEMG Upper Limb Motion Intention Recognition-Reference-Cited by-同舟云学术

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A Multi-scale Temporal Convolutional Network-based Method for sEMG Upper Limb Motion Intention Recognition

Published:2022-09-23 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Intelligent Robotics and Control Engineering (IRCE)
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Author:

Zhu Yuxuan¹,Li Xing²,Wang Jianhui¹,Ji Ying³,Sun Yuechao¹

Affiliation:

1. School of Information Science and Engineering, Northeastern University,Shen Yang,China

2. School of Electrical Engineering & Intelligentization, Dongguan University of technology,Dong Guan,China

3. School of Information Science and Engineering, Shenyang Ligong University,Shenyang,China

Funder

National Natural Science Foundation of China

Liaoning Natural Science Foundation

Dongguan Science and Technology Specialists Project

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9962813/9962972/09963016.pdf?arnumber=9963016

Reference17 articles.

1. The Usefulness of Mean and Median Frequencies in Electromyography Analysis

2. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling;bai;ArXiv Preprint,2018

3. Residual Networks of Residual Networks: Multilevel Residual Networks

4. Weight normalization: A simple reparameterization to accelerate training of deep neural networks;salimans;Advances in neural information processing systems,0

5. Dropout: a simple way to prevent neural networks from overfitting;srivastava;The Journal of Machine Learning Research,2014

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