TY  - BOOK
AU  - Zhang,Xiang
AU  - Yao,Lina
TI  - Deep learning for EEG-Based Brain-Computer Interfaces: representations, algorithms and applications 
SN  - 9781786349583
AV  - QP360.7 .Z43 2022
U1  - 612.8/20285 23
PY  - 2022///
CY  - New Jersey
PB  - World Scientific
KW  - Brain-computer interfaces
KW  - Machine learning
N1  - Includes bibliographical references and index
N2  - "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 datasets. 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"--
ER  -