This error norm is based on the mean error norm of the optimised CDF for each resampled (replicate) data series.
It can also been explained by the fact that the population norm is based on the general population, which includes patients with and without psychiatric disorders.
The most established approach, the so-called L2 norm or classical minimum norm solution, minimizes the sum of squares of strength for all coactive sources, and the L1 norm is based on the sum of rectified source strengths (Ilmoniemi 1993; Hämäläinen and Ilmoniemi 1994; Fuchs et al. 1999).
The written norm was based on one that had developed in the manuscripts of central Sweden, extending from the Vadstena monastery in eastern Götaland to Stockholm and Uppsala.
Note that these norms are based on a student sample, rather than a general population sample.
ℓ2,1-norm is based on the postulate that the features from the same class will have a common sparsity pattern in the feature space.
The theory of dynamic norms is based on principles of dynamic comparability and subordination of development indicators that is incomparable in the statistics characteristics of the economy became comparable in dynamic.
The currently most common approach to behavioral norms is based on game theory and relates the issue to ultimatum games [62], [65], [78], stag hunt games [81], [82], prisoner's dilemmas [15], [47], [69], [83], [84], or related concepts [58].
Current norms are based on this visual scaling.
Subjective norms are based on perceptions of the views of other individuals or groups (normative beliefs), and the strength of the individual's desire to gain approval of these groups (motivation to comply).
