能够轻松地调整内容的显示方式，这一点也很重要；我们需要在开发的迭代过程和未来的任何调整期间保持灵活性。
The ease of adjusting the way the content was displayed was crucial; we needed to remain flexible during iterations of the design and any future adjustments.
它是迭代生命周期与使收集和应用成为可能的适当测试过程的交汇点。
It is the intersection of an iterative lifecycle with an appropriate testing process that makes collection and application possible.
在迭代过程中有数据集汇聚成单点，叫做吸性不动点。
There are data sets in iteration that converge to single points, called attractive fixed points.
文章推荐的应用软件在电厂测试数据的基础上，经过反复迭代，可求出在某些控制点上的优化燃烧过程，从而可显著提高电厂效率。
From test data generated in power stations a strategy can be developed to optimise the combustion process in iterative steps at individual control points.
提出了一种求解线性规划(LP)的改进的单纯形法，其迭代过程产生的一部分极点可能出现在可行域外成为不可行极点，因此称之为外点单纯形法。
This paper presents an improved (infeasible) simplex method for linear programming, in which some of vertex points, corresponding to the iterative process, can be out of the feasible domain of (LP).
修正PCA算法能够在运行过程中自动地识别样本集之中的“劣点”，从而通过迭代计算加以适当处理来排除对运算精度的影响。
The new robust PCA algorithm can recognize the outliers in the sample set automatically and exterminate their effects to the accuracy of the PCA algorithm through proper processing to the outliers.
一旦迭代过程收敛，通过对点扩散函数进行傅立叶变换即可得到待测低分辨率图像的MTF。
Once the process has converged, taking the Fourier Transform of the PSF gives the estination of the low resolution image MTF.
本文对于矩形区域上某一内点为奇点的奇异积分的近似计算给出了优化中心数值算法，它在迭代计算过程中避免了函数值的重复计算。
This paper presents an optimum numerical algorithm of center rule for the approximate evaluation of singular integrals over rectangular domains with a inner singularity.
该鲁棒pca算法能够在运行过程中自动地识别样本集之中的“劣点”，从而在迭代训练中加以适当处理来排除对运算精度和收敛性的影响。
The new robust PCA algorithm can recognize the outliers in the sample set automatically and exterminate their effects to the accuracy of the PCA algorithm through proper processing to the outliers.
该鲁棒pca算法能够在运行过程中自动地识别样本集之中的“劣点”，从而在迭代训练中加以适当处理来排除对运算精度和收敛性的影响。
The new robust PCA algorithm can recognize the outliers in the sample set automatically and exterminate their effects to the accuracy of the PCA algorithm through proper processing to the outliers.
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