EEG Signal Processing and Feature Extraction

Author:   Li Hu ,  Zhiguo Zhang
Publisher:   Springer Verlag, Singapore
Edition:   1st ed. 2019
ISBN:  

9789811391156


Pages:   437
Publication Date:   25 October 2020
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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EEG Signal Processing and Feature Extraction


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Author:   Li Hu ,  Zhiguo Zhang
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2019
Weight:   0.682kg
ISBN:  

9789811391156


ISBN 10:   9811391157
Pages:   437
Publication Date:   25 October 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- EEG: origin and measurement.- Electroencephalography, Evoked potentials and event-related potentials.- ERP Experimental design.- EEG Preprocessing and denoising.- Spectral and time-frequency analysis.- Blind source separation.- Microstate analysis.- Source analysis.- Single-trial analysis.- Nonlinear neural dynamics.- Connectivity analysis.- Spatial complex brain network.- Temporal complex network analysis.- Machine learning.- Deep learning.- Statistical analysis.- Simultaneous EEG-fMRI.- EEG/ERP data analysis toolboxes.- Summary and conclusions.

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Author Information

Dr. Li Hu is a Principle Investigator at the Institute of Psychology, Chinese Academy of Sciences, China. He is also an Honorary Senior Research Associate at University College London. Dr. Hu has contributed to the development of novel techniques to facilitate the analysis of event-related EEG responses. He has published more than 60 research articles in this field, and was sponsored by the National Natural Science Foundation of China for Excellent Young Scholars. Dr. Zhiguo Zhang is a Professor at the School of Biomedical Engineering, Health Science Center, Shenzhen University, China. His research focuses on neural signal analysis, brain-computer interaction, machine learning for brain decoding and digital signal processing. He has published more than 60 articles in these fields.

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