Study of Feature Extraction Techniques for BCI Processing-Reference-Cited by-同舟云学术

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Study of Feature Extraction Techniques for BCI Processing

Published:2022-12-23 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)
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Author:

Sudheer Devulapalli¹^ORCID,N Jothiaruna²^ORCID,Potti Anupama³^ORCID,M Gangappa¹,RamaSubbareddy Somula⁴^ORCID

Affiliation:

1. Computer Science and Engineering VNR VJIET,Hyderabad,India

2. Vellore. Institute of Technology,Schoolf Computer Science and Enginerring,Vellore,Tamilnadu

3. Sree Dattha Institute of Engineering and Science,Computer Science and Engineering,Hyderabad,India

4. VNR VJIET,Dept. Information Technology,Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10083316/10083513/10084335.pdf?arnumber=10084335

Reference16 articles.

1. DWT and CNN based multi-class motor imagery electroencephalographic signal recognition

2. Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI

3. Remote sensing image retrieval by integrating automated deep feature extraction and handcrafted features using curvelet transform

4. Parallel Spatial–Temporal Self-Attention CNN-Based Motor Imagery Classification for BCI

5. BCI decoder performance comparison of an LSTM recurrent neural network and a Kalman filter in retrospective simulation

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