Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications
  • Release Date : 14 September 2021
  • Publisher : World Scientific
  • Genre : Computers
  • Pages : 296 pages
  • ISBN 13 : 9781786349606
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Download or read book entitled Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications by author: Xiang Zhang which was release on 14 September 2021 and published by World Scientific with total page 296 pages . This book available in PDF, EPUB and Kindle Format. Deep Learning for EEG-Based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms and applications. BCI bridges humanity's neural world and the physical world by decoding an individuals' brain signals into commands recognizable by computer devices.This book presents a highly comprehensive summary of commonly-used brain signals; a systematic introduction of around 12 subcategories of deep learning models; a mind-expanding summary of 200+ state-of-the-art studies adopting deep learning in BCI areas; an overview of a number of BCI applications and how deep learning contributes, along with 31 public BCI data sets. The authors also introduce a set of novel deep learning algorithms aimed at current BCI challenges such as robust representation learning, cross-scenario classification, and semi-supervised learning. Various real-world deep learning-based BCI applications are proposed and some prototypes are presented. The work contained within proposes effective and efficient models which will provide inspiration for people in academia and industry who work on BCI.

Brain Computer Interfaces

Brain Computer Interfaces

Author : Theodore W. Berger,John K. Chapin,Greg A. Gerhardt,Dennis J. McFarland,Jose C. Principe,Walid V. Soussou,Dawn M. Taylor,Patrick A. Tresco
Publisher : Springer Science & Business Media
Genre : Technology & Engineering
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