Data aggregation strategies for a P300 speller: decoding models, epoch averaging, cross-subject ensembles, and multi-channel models
- DOI
- 10.64898/2026.06.17.732982
- Published
- 2026-06-22
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- openRxiv
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.64898/2026.06.17.732982,
title = {Data aggregation strategies for a P300 speller: decoding models, epoch averaging, cross-subject ensembles, and multi-channel models},
author = {Leonid Sidorov and Anna Makarova and Archil Maysuradze and Mikhail Lebedev},
year = {2026},
doi = {10.64898/2026.06.17.732982},
url = {https://doi.org/10.64898/2026.06.17.732982}
}RIS
TY - JOUR TI - Data aggregation strategies for a P300 speller: decoding models, epoch averaging, cross-subject ensembles, and multi-channel models AU - Leonid Sidorov AU - Anna Makarova AU - Archil Maysuradze AU - Mikhail Lebedev PY - 2026 DO - 10.64898/2026.06.17.732982 UR - https://doi.org/10.64898/2026.06.17.732982 ER -
APA
Sidorov, L., Makarova, A., Maysuradze, A., & Lebedev, M. (2026). Data aggregation strategies for a P300 speller: decoding models, epoch averaging, cross-subject ensembles, and multi-channel models. https://doi.org/10.64898/2026.06.17.732982
Source records
- crossref · retrieved 2026-09-25T07:49:37.189Z