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Author:   Wanzeng Kong ,  Xuanyu Jin
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9789819645114

ISBN 10:   9819645115
Pages:   194
Publication Date:   19 July 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Chapter 1 Overall of Brain Fingerprint Identification.- Chapter 2 Basics of EEG Signals.- Chapter 3 Multi-Task Brain Fingerprint Identification Based on Brain Networks.- Chapter 4 Multi-Task Brain Fingerprint Identification Based on Low-Rank and Sparse Decomposition Model.- Chapter 5 Multi-Task Brain Fingerprint Identification Based on Residual and Multi-scale Spatio-temporal Convolution Neural Network (RAMST-CNN).- Chapter 6 Multi-Task Brain Fingerprint Identification Based on Convolutional Tensor-Train Neural Network (CTNN).- Chapter 7 Specific-Task and Multi-Session Brain Fingerprint Identification Based on Multi-scale Convolution and Graph Pooling Network (MCGP).- Chapter 8 Multi-Task and Multi-Session Brain Fingerprint Identification Based on Tensorized Spatial-Frequency Attention Network with Domain Adaptation (TSFAN).- Chapter 9 Task-independent Cross-Session Brain Fingerprint Identification Based on Disentangled Adversarial Generalization Network (DAGN).- Chapter 10 Summary.

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Author Information

Wanzeng Kong is currently a professor at the School of Computer Science, Hangzhou Dianzi University, and the director of the Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province. He received his Ph.D. degree from the Department of Electrical Engineering, Zhejiang University, in 2008. He was a visiting research associate at the Department of Biomedical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA, from 2012 to 2013. He was awarded the Top 2% Scientists Worldwide in both 2023 and 2024, and also received the Best Researcher Award at the 2nd Edition of International Research Awards on Internet of Things and Applications. His research interests include brain-machine collaborative intelligence, brain–computer interface, machine learning, pattern recognition, and cognitive computing. Xuanyu Jin is a postdoctoral researcher at the School of Automation (School of Artificial Intelligence), Hangzhou Dianzi University. She received her Ph.D. degree from the School of Computer Science, Hangzhou Dianzi University in 2024. Her research interests include brain-computer interface, tensor learning, and transfer learning.

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