Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based
  Generative Models for Improved SSVEP Classification   Despite significant recent progress in the area of Brain-Computer Interface
(BCI), there are numerous shortcomings associated with collecting
Electroencephalography (EEG) signals in real-world environments. These include,
but are not limited to, subject and session data variance, long and arduous
calibration processes and predictive generalisation issues across different
subjects or sessions. This implies that many downstream applications, including
Steady State Visual Evoked Potential (SSVEP) based classification systems, can
suffer from a shortage of reliable data. Generating meaningful and realistic
synthetic data can therefore be of significant value in circumventing this
problem. We explore the use of modern neural-based generative models trained on
a limited quantity of EEG data collected from different subjects to generate
supplementary synthetic EEG signal vectors, subsequently utilised to train an
SSVEP classifier. Extensive experimental analysis demonstrates the efficacy of
our generated data, leading to improvements across a variety of evaluations,
with the crucial task of cross-subject generalisation improving by over 35%
with the use of such synthetic data.

3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph