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Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency

Abstract A novel hybrid approach combining neighborhood component analysis (NCA) and metaheuristic optimization algorithms is proposed to improve the classification accuracy of electromyography (EMG) signals while reducing the feature set size and computational time. EMG signals were collected from...

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Principais autores: X. Little Flower, S. Poonguzhali
Formato: Artigo
Idioma:Inglês
Publicado em: SpringerOpen 2025-05-01
coleção:Journal of Electrical Systems and Information Technology
Assuntos:
Gray wolf optimization
Equilibrium optimization
Neighborhood component analysis
K-nearest neighbor
Metaheuristic algorithm
Acesso em linha:https://doi.org/10.1186/s43067-025-00205-0
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