Sentence examples for convergence errors from inspiring English sources

We then propose several strategies for the design of numerical schemes which reduce these convergence errors.

Both round-off and iterative convergence errors are discussed, and a posteriori methods for estimating the discretization error are examined.

No convergence errors were found in the 256 array system, but with new RRAM array systems reaching higher density, applicability of the model there remains a question.

In this paper we investigate several methods to numerically approximate nonconservative hyperbolic systems, we discuss why these convergence errors arise, and by using recent results established by Alouges and Merlet we give an approximate description of what weak solutions these numerical solutions converge to.

Furthermore, unlike the method proposed by McShane et al. [ 5] to correct for measurement error in continuous exposures, the Bayesian method proposed in this paper is neither prone to convergence errors nor highly dependent on the settings of a particular individually matched case-control study.

The proposed algorithm converges very fast, so that only in its first iteration, the convergence error is less than 0.2%.

The convergence error is set to 0.001.

It is then used to obtain an a priori estimate of the convergence error.

In Section 2, under the a posteriori parameter choice rule, we give the convergence error estimate.

B: the convergence error on a binary tree of depth 16 (65,536 nodes).

Statistical convergence error is defined and monitored by using the confidence intervals of the mean and variance.