Description

• Title:
  Hybrid implementation of the fastICA algorithm for high-density EEG using the capabilities of the intel architecture and CUDA programming
• Creator:
  Gajos-Balińska, Anna;
  Wójcik, Grzegorz M.;
  Stpiczyński, Przemysław
• Description:
  High-density electroencephalographic (EEG) systems are utilized in the study of the human brain and its underlying behaviors. However, working with EEG data requires a well-cleaned signal, which is often achieved through the use of independent component analysis (ICA) methods. The calculation time for these types of algorithms is the longer the more data we have. This article presents a hybrid implementation of the fastICA algorithm that uses parallel programming techniques (libraries and extensions of the Intel processors and CUDA programming), which results in a significant acceleration of execution time on selected architectures.
• Object availability:
  free access
• Rights:
  Copyright (c) 2023 Computer Science;
  https://creativecommons.org/licenses/by/4.0
• Date:
  2023.10.19
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion;
  Peer-reviewed Article
• Language:
  English
• Source:
  Computer Science; Vol. 24 No. 4;
  2300-7036;
  1508-2806
• Format:
  application/pdf
• Publisher:
  AGH University of Krakow, Faculty of Computer Science
• Relation: https://journals.agh.edu.pl/csci/article/view/5539/2965
• Identifier: https://journals.agh.edu.pl/csci/article/view/5539 ;
  10.7494/csci.2023.24.4.5539
• Data provider:
  AGH University of Science and Technology Journals
• Can I use it?:
  seek permission
• Type:
  text