A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Estimating evoked dipole responses in unknown spatially correlated noise with EEG/MEG arrays
2000
IEEE Transactions on Signal Processing
We present maximum likelihood (ML) methods for estimating evoked dipole responses using electroencephalography (EEG) and magnetoencephalography (MEG) arrays, which allow for spatially correlated noise between sensors with unknown covariance. The electric source is modeled as a collection of current dipoles at fixed locations and the head as a spherical conductor. We permit the dipoles' moments to vary with time by modeling them as linear combinations of parametric or nonparametric basis
doi:10.1109/78.815475
fatcat:jv2q7lonwjeh5oub7x4ofodubi