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Chunk #333 — 4 Performance analysis — 4.2 Monte Carlo performance analysis of non-parametric inverse solutions — 4.2.1 Inverse solutions

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Review on solving the inverse problem in EEG source analysis.
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These techniques were described in detail in earlier sections, thus they will not be described again here. For the SLF algorithm, however, the authors would like to point out that during the smoothing process, nodes at the boundary of the solution space were not smoothed as they have a limited amount of neighbours attributed to them. Also the recursive procedure was repeated until one of the following conditions was true: i) the number of prominent nodes in the solution space is less than the number of sensors, ii) the difference between the norms of consecutive current densities is less than 0.001, iii) the number of prominent nodes increases from one iteration to the next.