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  1. Home
  2. Volume 7, Issue 2
  3. Authors

Online ISSN: 2515-8260

Volume7, Issue2

BRAIN COMPUTER INTERFACE SYSTEM USING DEEP CONVOLUTIONAL MACHINE LEARNING METHOD

    Dr. Vikas Jain Dr.S. Kirubakaran Dr.G. Nalinipriya Binny. S Dr.M. Maragatharajan

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 2, Pages 3294-3301

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Abstract

Brain-computer interface (BCI) decoding connects the human nervous world to the external world.
People's brain signals to commands that computer devices can detect. In-depth study the performance
of brain-computer interface systems has recently increased. In this article, we will systematically
Investigate brain signal types for BCI and explore relevant in-depth study concepts for brain signal
analysis. In this study, we have a comparison of different traditional classification algorithms new
methods of in-depth study. We explore two different types Deep learning methods, i.e., traditional
neural networks Architecture with Long Short term Memory and Repetitive Neural Networks. We
check the classification Accuracy of Recent 5-Class Study-State Visual Evoked Opportunities dataset.
The results demonstrate in-depth expertise learning methods compared to traditional taxonomy
Algorithms.
Keywords:
    Deep Learning Brain Computer Interface neural network Taxonomy Algorithm Classification
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(2020). BRAIN COMPUTER INTERFACE SYSTEM USING DEEP CONVOLUTIONAL MACHINE LEARNING METHOD. European Journal of Molecular & Clinical Medicine, 7(2), 3294-3301.
Dr. Vikas Jain; Dr.S. Kirubakaran; Dr.G. Nalinipriya; Binny. S; Dr.M. Maragatharajan. "BRAIN COMPUTER INTERFACE SYSTEM USING DEEP CONVOLUTIONAL MACHINE LEARNING METHOD". European Journal of Molecular & Clinical Medicine, 7, 2, 2020, 3294-3301.
(2020). 'BRAIN COMPUTER INTERFACE SYSTEM USING DEEP CONVOLUTIONAL MACHINE LEARNING METHOD', European Journal of Molecular & Clinical Medicine, 7(2), pp. 3294-3301.
BRAIN COMPUTER INTERFACE SYSTEM USING DEEP CONVOLUTIONAL MACHINE LEARNING METHOD. European Journal of Molecular & Clinical Medicine, 2020; 7(2): 3294-3301.
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