Analysis and Classification of EEG Signals for Brain– Computer Interfaces
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...
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Artificial Intelligence and Mobile Services – AIMS 2022
۱۱th International Conference Held as Part of the Services Conference Federation, SCF 2022 Honolulu, HI, USA, December...
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