Exact(1)
In the field of human speech capturing systems, a fundamental role is played by the source localization algorithms.
Similar(59)
We consider the ULA composed of M = 10 sensors separated by half a wavelength for the source localization problem.
As a limitation of the present study it can be noted that the selection of time windows for the source localization was informed by previous event-related potential studies (e.g. Leutgeb et al., 2009; Olofsson et al., 2008).
The source localization error is defined by e r angle ≜ ∑ i = 1 3 ( θ ^ i - θ i ) 2 ∕ 3 and the power estimation error is defined by e r power ≜ ∑ i = 1 3 ( p ^ i - p i ) 2 ∕ 3. Figure 3a, b, d, e represent histograms of er EIAA angle - er IAA angle and er EIAA power - er IAA power, and the triangles indicate the centroids of the histograms.
The source localization results are admittedly limited by the low spatial resolution of ERP.
The comparisons of the source localization results with noise-contaminated EEG measurements by using four different BSCRs are summarized in Figure 4.
The 'Source localization' section deals with the source localization issue.
The source localization algorithms of accumulated source imaging were based on recent reports on MEG source reconstruction [27].
In the present study, DCM was used to investigate 2 separate questions: First, BMS was used to identify that configuration of MEG sources identified by the VB-ECD source localization best explained the data in the time-window of interest (1 300 ms).
The spatio-temporal dynamics of intention decoding provided by the EEG and source localization methods used in the present study substantially supplement the results observed in the fMRI RS data.
Several attempts have been made to improve the spatial resolution of the scalp EEG by using source localization techniques that employ computational algorithms to "de-blur" the recorded scalp potentials.
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