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This dataset delivers 216 covariance matrices from EEG ERPs with 4 different known classes by types of sources. Among 60 channels, only 32 channels are taken and sample covariance matrix is computed for each participant. The data is taken from a Python library mne's sample data.

Usage

data(ERP)

Format

a named list containing

covariance

an \((32\times 32\times 216)\) array of covariance matrices.

label

a length-\(216\) factor of 4 different classes.

See also

Examples

# \donttest{
## LOAD THE DATA AND WRAP AS RIEMOBJ
data(ERP)
myriem = wrap.spd(ERP$covariance)
# }