Analysis and Classification of EEG Signals for Brain–Computer Interfaces (Studies in Computational Intelligence, 852, Band 852) - Hardcover

Buch 359 von 538: Studies in Computational Intelligence

Paszkiel

 
9783030305802: Analysis and Classification of EEG Signals for Brain–Computer Interfaces (Studies in Computational Intelligence, 852, Band 852)

Inhaltsangabe

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology.

In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Von der hinteren Coverseite

This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology.

In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Weitere beliebte Ausgaben desselben Titels

9783030305833: Analysis and Classification of EEG Signals for Brain–Computer Interfaces (Studies in Computational Intelligence, Band 852)

Vorgestellte Ausgabe

ISBN 10:  303030583X ISBN 13:  9783030305833
Verlag: Springer, 2020
Softcover