An enhanced classification scheme with AdaBoost concept in BCI

Author:

Kim June-Hyoung1,Yang Yeon-Mo2

Affiliation:

1. Graduate Program, Kumoh National Inst. of Tech.1 Yangho-dong, Gumi, Gyeongbuk, Korea

2. School of Electronic Eng., Kumoh National Inst. of Tech.1 Yangho-dong, Gumi, Gyeongbuk, Korea

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference23 articles.

1. Regularizing common spatial patterns to improve BCI designs: Unified theory and newalgorithms;Lotte;IEEE Trans Biomed Eng,2011

2. N.K.N. Aznan and Y.-M. Yang, Applying Kalman filter in EEG-based brain computer interface for motor imagery classification, IEEE International Conference on ICT Con- vergence (ICTC), 2013.

3. Motor-imagery EEG signal classification using posi- tion matching and vector quantization;Jang;Int J Telemedicine and Clinical Practices,2016

4. Noise reduction techniques using particle filters in brain computer inter- face systems;Choi;Int J Telemedicine and Clinical Practices,2016

5. The BCI competition III: Vali- dating alternative approaches to actual BCI problems;Blankertz;IEEE Trans Neural Syst Rehabil Eng,2006

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1. A Framework for Enhancing Classification in Brain–Computer Interface;Lecture Notes on Data Engineering and Communications Technologies;2022

2. Investigation of brain computer interface for rich multimedia environment;International Journal of Communication Systems;2020-08-20

3. Comparison of the effectiveness of automatic EEG signal class separation algorithms;Journal of Intelligent & Fuzzy Systems;2019-12-23

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