迭代的

Based on ear recognition, an improved NMFSC(Nonnegative Matrix Factorization with Sparseness Constraints) method was proposed by imposing an additional constraint on the objective function of NMFSC, which could capture the semantic relations of coefficient matrix as orthogonal as possible. The interated rules to solve the objective function with the constraint were presented, and its convergence was proved.

针对人耳识别问题，提出了一种改进的稀疏性受限的非负矩阵因子方法，通过增加一个使系数矩阵尽可能正交的约束条件来定义原目标函数，给出求解该目标函数的迭代规则，并证明迭代规则的收敛性。

Based on ear recognition, an improved NMFSC (Non-negative Matrix Factorization with Sparseness Constraints) method was proposed by imposing an additional constraint on the objective function of NMFSC, which could capture the semantic relations of coefficient matrix as orthogonal as possible. The interated rules to solve the objective function with the constraint were presented, and its convergence was proved.

针对人耳识别问题，提出了一种改进的稀疏性受限的非负矩阵因子方法，通过增加一个使系数矩阵尽可能正交的约束条件来定义原目标函数，给出求解该目标函数的迭代规则，并证明迭代规则的收敛性。

We construct some new iterative algorithms with errors for solving these generalized fuzzy variational inclusions by using the resolvent operator technique for maximal η-monotone mappings and prove the convergence of iterative sequences generated by the algorithms.

为了利用η-极大单调映象的预解算子技巧求解这类广义模糊变分包含，我们建立了一些新的含误差的迭代算法，并证明了由这类算法产生的迭代序列的收敛性。

In the proposed algorithm the traditional fixed step size iteration is substituted by time-varying step size iteration to improve the accuracy of directional estimation while the minimum mean square deviation is solved to achieve the purpose of increasing the convergence speed of the proposed algorithm.

以一种时变步长迭代方法取代传统的定步长迭代法，旨在提高算法在求取均方差最小值的过程中方向估值的精度，从而达到提高算法收敛速度的目的。

When the mean square deviation between point set obtained by iteration and attractor become the minimum, the prediction value can be used as the function value of the point to be extrapolated.

该算法利用内区间的迭代函数系和吸引子由特定初始点进行搜索，通过迭代使得到的点集与吸引子的均方偏差最小，从而获得需要外推点的函数值作为预测值。

By using accelerating Aitken method in iterative method of nonlinear equations, a new modified method is given. The method is applied to modified Newton method, thereby a new method is developed, which is faster and stable. Also, its algorithm is given. Numerical results show that the new method is very efficient.

通过对非线性方程组的迭代法引入Aitken加速技术，设计了一种非线性方程组的迭代解法的加速方法；将该方法与M步Newton法相结合，得到一种收敛速度快而且计算稳定的方法，并给出了具体算法；数值结果表明了新算法是有效的。

At present, many effective iterations are all derived from Newton method.

Newton法是求解非线性方程的一个最基本而且十分重要的迭代方法，目前使用的很多有效的迭代法，都是以Newton法为基础，并由它而得到的。

An iteration procedure for improving design variables is constructed by this optimality criterion, and a factor is also employed to control the step size in order to make the iterative process be stable.

根据导出的优化准则构造出一种修改设计变量的迭代格式，其中引入松弛因子以保证收敛过程的稳定，并在每次迭代开始前都利用射线步把设计点引至可行域的边界上。

One is introducing a weighting factor to reduce oscillation of solution of diagnosis equation in each iteration.

因此本文又进一步提出了改善诊断方程收敛性的措施，包括在迭代过程中引入加权因子来修正元件参数的调整量，以及根据诊断方程的解判断元件参数故障偏移的方向和大小对迭代初值进行调整。

Based on long term study, we put forward new algorithm of recognizing fingerprint directional diagram: the iterative algorithm based on model, which revises the singular points (central point and triangulation point) and fingerprint directional diagram through local and global iteration. Hence, the algorithm can recognize the directional diagram and singular point more accurately and can extract detail features more accurately.

经过长期的研究，我们提出全新的判别指纹方向图算法：基于模型的迭代算法，通过局部和全局反复迭代修正图像的奇异点和指纹方向图，更能准确地判断指纹方向图、奇异点，从而更能准确地提取细节特征点。

According to the clear water experiment, aeration performance of the new equipment is good with high total oxygen transfer coefficient and oxygen utilization ratio.

曝气设备的动力效率在叶轮转速为120rpm～150rpm时取得最大值，此时氧利用率和充氧能力也具有较高值。

The environmental stability of that world - including its crushing pressures and icy darkness - means that some of its most famous inhabitants have survived for eons as evolutionary throwbacks, their bodies undergoing little change.

稳定的海底环境─包括能把人压扁的压力和冰冷的黑暗─意谓海底某些最知名的栖居生物已以演化返祖的样态活了万世，形体几无变化。