Representation Learning for EEG-Based Biometrics Using Hilbert–Huang Transform

Representation Learning for EEG-Based Biometrics Using Hilbert–Huang Transform

A promising approach to overcome the various shortcomings of password systems is the use of biometric authentication, in particular the use of electroencephalogram (EEG) data. In this paper, we propose a subject-independent learning method for EEG-based biometrics using Hilbert spectrograms of the d...

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Bibliographic Details
Main Authors: Mikhail Svetlakov, Ilya Kovalev, Anton Konev, Evgeny Kostyuchenko, Artur Mitsel
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Computers
Subjects:
EEG
biometrics
multi-similarity loss
subject-independent
representation learning
Hilbert–Huang transform
Online Access:https://www.mdpi.com/2073-431X/11/3/47

Internet

https://www.mdpi.com/2073-431X/11/3/47

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