A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification

A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification

Features extracted from the electromyography (EMG) signal normally consist of irrelevant and redundant features. Conventionally, feature selection is an effective way to evaluate the most informative features, which contributes to performance enhancement and feature reduction. Therefore, this articl...

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Bibliographic Details
Main Authors: Jingwei Too, Abdul Rahim Abdullah, Norhashimah Mohd Saad, Nursabillilah Mohd Ali, Weihown Tee
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Computers
Subjects:
feature selection
electromyography
grey wolf optimizer
binary grey wolf optimization
classification
time-frequency feature
Online Access:https://www.mdpi.com/2073-431X/7/4/58

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