sEMG signal classification with novel feature extraction using different machine learning approaches
Author:
Affiliation:
1. Department of Electrical Engineering, National Institute of Technical Teachers Training and Research, Panjab University, Chandigarh, India
Publisher
IOS Press
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
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