离散化

Bilinear transformation was adopted to discrete the mathematic model of the whole simulation system. Considered that LabVIEW was a novel graphic computer language, the practical realization of mathematical model in LabVIEW was presented.

首先采用频率预曲折双线性变换法将控制系统的数学模型离散化；然后在LabVIEW中进行图形化编程，从而实现了基于虚拟仪器的汽轮机系统的仿真。

In order to effectively abstract the texture and denoise but not damage the edge and other important details of image, Meyer (2001) proposed using elements of BV space and G space to characterize cartoon and details of image respectively. The authors present PDE of minimizing energy on the basis of Meyer's work, After the model is discretizated. projection algorithm and the method for ROF model are applied. Thus an image is decomposed into two parts, bounded variation component u and texture with noise υ.

为有效地提取纹理和去噪而不损坏图像的边缘及其他重要细节，Meyer(2001)提出了分别用BV空间和G空间刻画图像的主体和细节部分，笔者在Meyer的图像分解模型基础上，建立能量最小化PDE方程，将模型离散化后，利用投影算法和ROF模型的求解方法，将图像分解为有界变差部分u和包含纹理和噪声的部分υ。

Traditional method to coarsen and disperse the spatial data to lower administer unit in order to let spatial data be agreement to statistic data loses some spatial information. The comprehensive indexes got from these data of course cannot express the land-use spatial differentiation regularity well.

传统的研究方法是将空间数据"粗化"和"离散化"到行政单元上，与统计数据匹配，结果失去了一些指标的空间分布信息，得到的综合评价指数并不能较好地反映区域土地利用的空间分异规律。

A theoretical model is presented which adopts maglev system to decompound complex problems in micro assembly and makes the system simple.

针对现有微装配系统存在的问题，给出了一种新的理论模型；将微产品装配离散化，便于建立标准化、模块化的实用微装配系统。

When distribution technology is used in it, aspects as dispersedness in space, parallelizability in time and data sharing are considered.

当其与分布式技术结合起来之后，更需要考虑空间离散化、时间并行化和数据共享等方面的问题。

In order to effectively Abstract the texture and denoise but not damage the edge and other important details of image,Meyer(2001) proposed using elements of BV space and G space to characterize cartoon and details of image respectively.The authors present PDE of minimizing energy on the basis of Meyer s work.

为有效地提取纹理和去噪而不损坏图像的边缘及其他重要细节，Meyer(2001)提出了分别用BV空间和G空间刻画图像的主体和细节部分，笔者在Meyer的图像分解模型基础上，建立能量最小化PDE方程，将模型离散化后，利用投影算法和ROF模型的求解方法，将图像分解为有界变差部分u和包含纹理和噪声的部分v。

Note that regularized problems are usually defined in an infinite setting and have to be discTetized for an implementation and there have been many comparatively adult methods of calculating singular system. Therefore, there is no need to avoid the calculation of singular system in inverse problems calculating of numeric value. Here TSVD Regularization Method is very simple and quite effective one.

考虑到反问题的数值计算需要将问题离散化，化为有限维的问题来进行处理，而对于有限维算子的奇异系的计算已经有了相当成熟的各种算法，因此在反问题的数值计算中没有必要避开奇异系的计算，此时TSVD正则化方法是十分简单并相当有效的正则化方法。

This paper introduced rough sets data mining method to take potential diagnosis rule from the fault diagnosis decision-making table of steam turbine unit. These rules can offer effective fault diagnosis service for steam turbine unit.

将汽轮机组故障历史数据进行模糊化及离散化处理，构建故障诊断决策表，以决策表作为主要工具，即"知识库"，采用模糊粗糙集数据挖掘方法直接从决策表中提取出潜在的诊断规则，为汽轮机组提供有效的故障诊断。

For convenience of finite element discretization and preserving symmetry of the stiffness matrix, approximation and symmetrization of the continuum equilibrium equations were conducted.

为了便于进行有限元离散化并保持总刚度矩阵的对称性对连续介质平衡方程进行了简化和对称化处理。

And then the spatial predicates,possibly used in SDMKD from GIS,are analyzed and listed.Subsequently,the formal expression of spatial assoc...

从G IS数据库中挖掘空间关联规则的主要问题是多层、多关系的规则挖掘问题，不同专题图层不同空间对象之间空间谓词的高效计算与存储表达是解决问题的关键；把空间关系非空间化，将连续数据离散化，从而把求解问题转换成布尔型关联规则问题进行讨论，基于此而探讨了一种通过SJI-P表组织空间谓词，然后根据目标对象的概念层级自顶向下、逐层细化的空间关联规则挖掘方法。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。