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Signal Processing and Machine Learning for Brain-Machine Interfaces (Control, Robotics and Sensors) (in English)
Toshihisa Tanaka
(Illustrated by)
·
Mahnaz Arvaneh
(Illustrated by)
·
Institution of Engineering & Technology
· Hardcover
Signal Processing and Machine Learning for Brain-Machine Interfaces (Control, Robotics and Sensors) (in English) - Tanaka, Toshihisa ; Arvaneh, Mahnaz
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Synopsis "Signal Processing and Machine Learning for Brain-Machine Interfaces (Control, Robotics and Sensors) (in English)"
Brain-machine interfacing or brain-computer interfacing (BMI/BCI) is an emerging and challenging technology used in engineering and neuroscience. The ultimate goal is to provide a pathway from the brain to the external world via mapping, assisting, augmenting or repairing human cognitive or sensory-motor functions. In this book an international panel of experts introduce signal processing and machine learning techniques for BMI/BCI and outline their practical and future applications in neuroscience, medicine, and rehabilitation, with a focus on EEG-based BMI/BCI methods and technologies. Topics covered include discriminative learning of connectivity pattern of EEG; feature extraction from EEG recordings; EEG signal processing; transfer learning algorithms in BCI; convolutional neural networks for event-related potential detection; spatial filtering techniques for improving individual template-based SSVEP detection; feature extraction and classification algorithms for image RSVP based BCI; decoding music perception and imagination using deep learning techniques; neurofeedback games using EEG-based Brain-Computer Interface Technology; affective computing system and more.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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