Sentence examples for using the different beamformers from inspiring English sources

These replicas were matched with the simulated covariance data using the different beamformers.

Instantaneous gamma amplitude in each voxel was obtained by applying the Hilbert transform to the band-pass filtered time series obtained using the LCMV beamformer algorithm.

Source analysis was performed using the Synthetic Aperture Magnetometry SAMM) beamformer algorithm, which is described in detail elsewhere (Robinson & Vrba, 1999; Vrba & Robinson, 2001; Hillebrand et al., 2005).

We describe and compare two different approaches: the first one is based on the generalized likelihood ratio test (GLRT) detector directly applied on the array snapshots, and the second one uses a digital beamformer as a spatial filter to mitigate the interferences and acquire the signal using the beamformer output.

The second approach uses a digital beamformer as a spatial filter to mitigate the interferences and then detect the signal using the beamformer output.

Sensor-level data were then spatially filtered using the beamformer weights at the location of interest to create a single timeseries per trial per participant per analysis.

We then used the SAM beamformer to produce volumetric images of source power for each condition (face and phase scrambled).

When the set of randomly generated beamformers is used, the set of receive beamformers has to be calculated at the receiver.

The sensor data were projected into source space using the linearly constrained minimum variance (lcmv) - beamformer technique onto a grid of 326 voxels with the size of 2 × 2 × 2 cm.

Finally, the beamformers are updated using the perturbation vector pair that gives the largest output power at the receiver.

Time courses were constructed using SAM beamformer coefficients obtained using the individual condition covariance matrices band-pass filtered between zero and 100 Hz [34].