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Uncertainties are calculated by applying parametric bootstrapping 1,000 times, excluding fits with poor convergence, and then taking the 2.5 97.5% range.
Truncation was performed, as this estimator is known to have poor convergence characteristics because MCMC samples with very low likelihoods have an unreasonable influence on the harmonic mean.
We argue that this instability is due to the poor convergence of the integrated D= 2 OPE series.
The predominant advantage of this technique is that it avoids the poor convergence or convergence failure problem caused by the weak perspective projection.
In particular, poor convergence and low similarity to the X-ray ensemble are seen for models calculated by CYANA from the HCNH NOEs alone (Fig. 4a, b; orange and red circles).
Despite its utility, due to the requirement of resolving fine structures, historically, numerical work has proven difficult and reported solutions were often plagued by poor convergence.
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Applications of the method to fractional differential equations (FDEs) mainly and directly used the Lagrange multipliers in ordinary differential equations (ODEs) which resulted in poor convergences.
The leaky LMS has the poorest convergence performance, primarily due to its inability to track the lowest frequencies.
The leaky LMS attenuates all frequencies (and not just those in violation of the constraint) and has the poorest convergence performance.
One can see that the PC and CSM approaches have poorer convergence property to the optimal SINR and lower SINR while the MSWF has better convergence performance, and the proposed approach has the fastest convergence rate.
The leaky LMS attenuates all frequencies (and not just those in violation of the constraint) and has the poorest convergence performance and highest excess misadjustment. Figure 7 Convergence comparison, gain-constrained condition, AR(1) colored noise input.
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