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Titlebook: Analysis and Classification of EEG Signals for Brain–Computer Interfaces; Szczepan Paszkiel Book 2020 Springer Nature Switzerland AG 2020

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發(fā)表于 2025-3-21 20:00:23 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Analysis and Classification of EEG Signals for Brain–Computer Interfaces
影響因子2023Szczepan Paszkiel
視頻videohttp://file.papertrans.cn/157/156155/156155.mp4
發(fā)行地址Presents a wealth of information on the development of brain–computer (BCI) technology with a particular focus on data acquisition methods and tools used for analyzing human brain activity.Highlights
學科分類Studies in Computational Intelligence
圖書封面Titlebook: Analysis and Classification of EEG Signals for Brain–Computer Interfaces;  Szczepan Paszkiel Book 2020 Springer Nature Switzerland AG 2020
影響因子.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.
Pindex Book 2020
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Data Analysis of Human Brain Activity Using MATLAB Environment with EEGLAB,r further processing. The data format (*.edf) is compatible with Toolbox EEGLAB It is an interactive tool within the Matlab environment for processing continuous data connected with EEG, MEG events and other electrophysiological data covering Independent Components Analysis (ICA), time analysis, fre
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發(fā)表于 2025-3-22 09:38:29 | 只看該作者
Using Neural Networks for Classification of the Changes in the EEG Signal Based on Facial Expressioers defined as automation of intellectual tasks performed by human beings. The consequences of the questions asked by the pioneers of informatics have been discovered until now in the form of many scientific and technological achievements. Artificial intelligence in itself is a very general discipli
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發(fā)表于 2025-3-22 16:47:25 | 只看該作者
Using BCI Technology for Controlling a Mobile Vehicle,installing the device software, a user receives a wide spectrum of possibilities in the aspect of the EEG signal analysis. The manufacturer provides appropriate software which enables real-time access to the signals from each of the electrodes installed in the device. The device communicates with a
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,Augmented Reality (AR) Technology in Correlation with Brain–Computer Interface Technology,ion can be seen in many cases, including the area of arts, culture and technological environment. In our case the latest range of immersion is the most important from the point of view of the technology discussed. Immersion in this range is connected directly with the electronics of advanced immersi
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