Linear Diophantine equation (LDE) decoder: A training‐free decoding algorithm for multifrequency SSVEP with reduced computation cost
نویسندگان
چکیده
Multifrequency steady-state visual evoked potentials (SSVEPs) have been developed to extend the capability of SSVEP-based brain-machine interfaces (BMIs) complex applications that large numbers targets. Even though various multifrequency stimulation methods introduced, decoding algorithms for SSVEP are still in early development. The recently canonical correlation analysis (MFCCA) was shown be a feasible training-free option use SSVEPs. However, time complexity MFCCA is O ( n 3 ) $$ O\left({n}^3\right) , which will lead long computation as grows, where represents input size decoding. In this paper, novel algorithm proposed with aim reduce complexity. This based on linear Diophantine equation solvers and has reduced cost l o g O(nlogn) while remaining training-free. Our simulation results demonstrated (LDE) decoder run only one fifth under respective optimal settings 5-s single-channel data. makes it easier implement real-time systems. effectiveness new validated nine healthy participants when using dry electrode scalp electroencephalography (EEG).
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ژورنال
عنوان ژورنال: Asian Journal of Control
سال: 2023
ISSN: ['1934-6093', '1561-8625']
DOI: https://doi.org/10.1002/asjc.3050