MEG beamforming using Bayesian PCA for adaptive data covariance matrix regularization.
Beamformers are a commonly used method for doing source localization from magnetoencephalography (MEG) data. A key ingredient in a beamformer is the estimation of the data covariance matrix. When the noise levels are high, or when there is only a small amount of data available, the data covariance m...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2011
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