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Now that we have seen the prominent approaches to both norm emergence and norm stability, we can turn to some general interpretive considerations of evolutionary models.
We implemented both norm smoothing and curvature smoothing methods for NMR T2 inversion, and compared the inversion results with respect to the optimal regularization parameters (α opt) which were selected by the discrepancy principle (DP), generalized cross-validation (GCV), S-curve, L-curve, and the slope of L-curve methods, respectively.
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Thus, agent platforms must provide normative support, allowing both norm-aware and non-norm-aware agents to take part in MAS that are controlled by norms.
Obviously, a continuous process and a weak continuous process are both norm-to-weak continuous processes.
According to this model, participants judge the protagonist not to have acted intentionally in both norm-conforming and norm-violating cases.
Rasch modeling is both norm-referenced (comparing individuals to the group) and criterion-referenced (measured according to specific standards; Siegel and Ranney 2003).
In this paper, a novel robust delay-dependent guaranteed cost controller is introduced for a class of uncertain nonlinear neutral systems with both norm-bounded uncertainties and nonlinear parameter perturbations.
In AURA, both norm-one (maximum column sum) and norm-infinity (maximum row sum), which are defined as (|C|_{1} = text {max}_{k}sum _{j}|c_{jk}|) and (|C|_{infty } = text {max}_{j}sum _{k}|c_{jk}|), respectively, are used.
It is well known that both norms are equivalent and (ell_{Phi}) is a Banach space [19, 20].
With this property, it is easy to check the (w^ -sequential low^ -sequentialuity for the (w^)-nulowerpe functionsemicontinuityms, the Luxemburg and the Orlicz norm.
We will write ℓ M (w), when the statement holds for the weighted Orlicz sequence space equipped with both norms - Luxemburg and Amemiya.
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