EEG-Driven Biometric Authentication for Investigation of Fourier Synchrosqueezed Transform-ICA Robust Framework
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-07798-6.pdf
Reference61 articles.
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3. Moctezuma, L.A.; Molinas, M.: Towards a minimal EEG channel array for a biometric system using resting-state and a genetic algorithm for channel selection. Sci. Rep. 10, 14917 (2020). https://doi.org/10.1038/s41598-020-72051-1
4. Jayarathne, I.; Cohen, M.; Amarakeerthi, S.: Person identification from EEG using various machine learning techniques with interhemispheric amplitude ratio. PLoS ONE 15, 1–24 (2020). https://doi.org/10.1371/journal.pone.0238872
5. Walia, G.S.; Singh, T.; Singh, K.; Verma, N.: Robust multimodal biometric system based on optimal score level fusion model. Expert Syst. Appl. 116, 364–376 (2019). https://doi.org/10.1016/j.eswa.2018.08.036
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1. Fourier Synchrosqueezing Transform-ICA-EMD Framework Based EOG-Biometric Sustainable and Continuous Authentication via Voluntary Eye Blinking Activities;Biomimetics;2023-08-18
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