Band power feature part-based convolutional neural network with African vulture optimization fostered channel selection for EEG classification-Reference-Cited by-同舟云学术

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Band power feature part-based convolutional neural network with African vulture optimization fostered channel selection for EEG classification

Published:2024-06-22 Issue: Volume: Page:1-14
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Selvaraj Vairaprakash¹,Alagarsamy Manjunathan²,Datchanamoorthy Kavitha³,Manickam Geethalakshmi⁴

Affiliation:

1. Department of Electronics and Communication Engineering, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India

2. Department of Electronics and Communication Engineering, K. Ramakrishnan College of Technology, Trichy, Tamil Nadu, India

3. Department of Computer Science and Engineering, Easwari Engineering College, Chennai, Tamil Nadu, India

4. Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2024.2356633

Reference33 articles.

1. African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems

2. Attention-Inception and Long Short-Term Memory-based Electroencephalography Classification for Motor Imagery Tasks in Rehabilitation

3. Deep Learning Models for Classification of Motor Imagery EEG Signals

4. The non-invasive Berlin Brain–Computer Interface: Fast acquisition of effective performance in untrained subjects

5. Convolutional Neural Network Based Approach Towards Motor Imagery Tasks EEG Signals Classification

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