A machine learning based method for classification of fractal features of forearm sEMG using Twin Support vector machines
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IEEE
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http://xplorestaging.ieee.org/ielx5/5608545/5625939/05627902.pdf?arnumber=5627902
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. CTSVM: A robust twin support vector machine with correntropy-induced loss function for binary classification problems;Information Sciences;2021-06
2. Classification of Daily-Life Grasping Activities sEMG Fractal Dimension;Proceedings of the 6th Brazilian Technology Symposium (BTSym’20);2021
3. Feature Selection Using Sparse Twin Support Vector Machine with Correntropy-Induced Loss;Knowledge Science, Engineering and Management;2020
4. Machine Learning Techniques for Predicting Surface EMG Activities on Upper Limb Muscle: A Systematic Review;Cyber Security and Computer Science;2020
5. EMG-Based Classification of Forearm Muscles in Prehension Movements: Performance Comparison of Machine Learning Algorithms;Cyber Security and Computer Science;2020
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