Can I read Deep learning for EEG-based brain-computer interfaces : representations, algorithms and applications on EtoBox?

Deep learning for EEG-based brain-computer interfaces : representations, algorithms and applications by Xiang Zhang, Lina Yao is a nonfiction available to read on EtoBox.

What is Deep learning for EEG-based brain-computer interfaces : representations, algorithms and applications about?

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

Who reads Deep learning for EEG-based brain-computer interfaces : representations, algorithms and applications?

Author

Xiang Zhang, Lina Yao

Publisher

World Scientific Publishing Co. Pte. Ltd

Published

2021

Language

EN

ISBN

9781786349583

Category

nonfiction

Subjects

Medical, Computer Science, Artificial Intelligence (Ai)