Ensemble Learning Approach to Motor Imagery EEG Signal Classification-Reference-Cited by-同舟云学术

Ensemble Learning Approach to Motor Imagery EEG Signal Classification

Published:2019 Issue: Volume: Page:183-208
ISSN:
Container-title:Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
language:
Short-container-title:

Author:

Chatterjee Rajdeep,Datta Ankita,Sanyal Debarshi Kumar

Publisher

Elsevier

Reference56 articles.

1. Study of Electroencephalographic Signal Processing and Classification Techniques Towards the Use of Brain-Computer Interfaces in Virtual Reality Applications;Lotte,2008

2. Brain-computer interface technology: a review of the first international meeting;Wolpaw;IEEE Trans. Rehabil. Eng.,2000

3. Brain-Computer Interfacing: An Introduction;Rao,2013

4. Performance analysis of ensemble methods for multi-class classification of motor imagery EEG signal;Bhattacharyya,2014

5. Ensemble classifiers and their applications: a review;Rahman,2014

Cited by 32 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Survey on Signal Processing and Classification Algorithms for Depression Using Electroencephalogram Signals;2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC);2024-06-28

2. Enhancing MI EEG Signal Classification With a Novel Weighted and Stacked Adaptive Integrated Ensemble Model: A Multi-Dataset Approach;IEEE Access;2024

3. Stacked ensemble deep learning for pancreas cancer classification using extreme gradient boosting;Frontiers in Artificial Intelligence;2023-10-09

4. An improved breast cancer disease prediction system using ML and PCA;Multimedia Tools and Applications;2023-09-25

5. A Machine Learning Approach for Polymer Classification Based on the Thermal Response under Data Scarcity─Tested on PMMA;Industrial & Engineering Chemistry Research;2023-06-29