Advanced electroencephalography analytical methods (15 Ergebnisse)

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Zustand: New. Ganesh Naik, ranked in the top 2% of researchers in Biomedical Engineering (Stanford University Research), is a leading expert in biomedical engineering and signal processing. He received his Ph.D. degree in Electronics Engineering, spec.

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Taschenbuch. Zustand: Neu. Neuware - Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using non-linear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience.This book: - Includes a comprehensive review on biomedical signals nature and acquisition aspects - Focuses on selected applications of neuroscience/cardiovascular/muscle-related biomedical areas - Provides a machine learning update to a classical biomedical signal processing approach - Explains deep learning and application to biomedical signal processing and analysis - Explores relevant biomedical engineering and neuroscience state-of-the-art applications This book is intended for researchers and graduate students in biomedical signal processing, electrical engineering, neuroscience, and computer science. …

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Hardback. Zustand: New. Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using non-linear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience.This book:Includes a comprehensive review on biomedical signals nature and acquisition aspectsFocuses on selected applications of neuroscience/cardiovascular/muscle-related biomedical areasProvides a machine learning update to a classical biomedical signal processing approachExplains deep learning and application to biomedical signal processing and analysisExplores relevant biomedical engineering and neuroscience state-of-the-art applicationsThis book is intended for researchers and graduate students in biomedical signal processing, electrical engineering, neuroscience, and computer science. …

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Hardback. Zustand: New. Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using non-linear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience.This book:Includes a comprehensive review on biomedical signals nature and acquisition aspectsFocuses on selected applications of neuroscience/cardiovascular/muscle-related biomedical areasProvides a machine learning update to a classical biomedical signal processing approachExplains deep learning and application to biomedical signal processing and analysisExplores relevant biomedical engineering and neuroscience state-of-the-art applicationsThis book is intended for researchers and graduate students in biomedical signal processing, electrical engineering, neuroscience, and computer science. …