A Comparative Work of Incremental Learning and Ensemble Learning for Brainprint Identification
Electroencephalogram (EEG) signals are nonstationary and vary across time. The static learning model requires large training data to ensure sufficient knowledge acquisition to build a robust model. However, it is very challenging to achieve complete concept learning due to the behavioural changes i...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Asian Research Publishing Network (ARPN)
2023
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/42567/3/A%20COMPARATIVE.pdf http://ir.unimas.my/id/eprint/42567/ http://www.arpnjournals.com/jeas/volume_11_2023.htm |
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