Little Flower, X., & Poonguzhali, S. (2025). Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency. Journal of Electrical Systems and Information Technology, 12(1). https://doi.org/10.1186/s43067-025-00205-0
ISO-690 (author-date, English)LITTLE FLOWER, X. und POONGUZHALI, S., 2025. Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency. Journal of Electrical Systems and Information Technology. 1 Dezember 2025. Vol. 12, no. 1, . DOI 10.1186/s43067-025-00205-0.
Modern Language Association 9th editionLittle Flower, X., und S. Poonguzhali. „Boosting EMG Classification: A Hybrid NCA-Driven Evolutionary Optimization Approach for High Accuracy and Efficiency“. Journal of Electrical Systems and Information Technology, Bd. 12, Nr. 1, Dezember 2025, https://doi.org/10.1186/s43067-025-00205-0.
Mohr Siebeck - Recht (Deutsch - Österreich)Little Flower, X./Poonguzhali, S.: Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency, Journal of Electrical Systems and Information Technology 2025,
Emerald - HarvardLittle Flower, X. und Poonguzhali, S. (2025), „Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency“, Journal of Electrical Systems and Information Technology, Vol. 12 No. 1, verfügbar unter:https://doi.org/10.1186/s43067-025-00205-0.