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Image of - Advanced Electroencephalography Analytical Methods Fundamentals Acquisition And Applications | Hardcover
Advanced Electroencephalography Analytical Methods Fundamentals Acquisition And Applications | Hardcover

Advanced Electroencephalography Analytical Methods Fundamentals Acquisition And Applications | Hardcover

by Naik G

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. The book: · Includes a comprehensive review on biomedical signals nature and acquisition aspects · Focuses on selected applications of neurosciences/ 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

Highlights

  • binding-icon

    9781032171708

    ISBN:

  • binding-icon

    Naik G

    Author:

  • binding-icon

    268

    Pages:

  • binding-icon

    572 gm

    Weight:

  • langauage-icon

    English

    Language:

  • date-icon

    2025

    Year:

  • edition-icon

    1st Edition

    Edition:

  • binding-icon

    Hardcover

    Binding:

₹9408

₹11760

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. The book: · Includes a comprehensive review on biomedical signals nature and acquisition aspects · Focuses on selected applications of neurosciences/ 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

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