Error models and data normalization techniques for high-resolution array technologies will be presented.
展示高分辨率阵列技术的误码模型和数据规范化技术。
So data normalization methods described above should be carefully used in distance cluster analysis for exploratory data.
因此，在对开发性数据进行距离聚类分折时，上述数据标准化方法应该谨慎使用。
On the basis of the error model, the paper also analyzes the application of data normalization algorithm to estimating fundamental matrix.
针对所建立的误差模型，分析数据规范化算法在基础矩阵估计中的应用。
Three major principles for the selection of indicator data normalization methods in multi-attribute evaluation are presented in this paper.
提出学术期刊综合评价中指标数据标准化方法选择的三大原则，即同一指标内部数据相对差距不变原则；
The technique of data normalization is about correct ways of partitioning the data among tables to minimize data redundancy and maximize the speed of retrieval.
数据正规化技术是为将数据正确地保存再各个标准，从而使数据冗余达到最小，存取速度达到最高。
And these methods are computationally expensive as they employ pre-process procedures including chip data normalization and other sophisticated statistical techniques.
而且这些方法由于使用了过多的预处理程序如数据归一化等其他复杂的统计方法，使得计算量非常大。
Based on this model both zero and gain drifts of the input channel can be corrected and its nonlinearity can be offset. Furthermore, the data normalization can also be done.
借此模型，克服零点漂移及增益漂移对检测精度的影响，补偿信号输入通道的非线性，实现了数据的规范化处理。
Data normalization is always recommended in theory, but in practice over-normalization (or normalization without appropriate de-normalization) lead to reliance on joins for data retrieval.
从理论上来说，总是建议您保证数据的规范化；但是在实践中，过度的规范化(或者没有恰当反规范化的规范化)会导致对数据检索连接的依赖性。
Then, the processes of computing the vector values of POI objects are discussed by the methods of questionnaire survey, multi-density spatial clustering and data normalization respectively.
然后，分别讨论了利用问卷调查、多密度空间聚类和数据规格化的方法计算POI对象的各项显著性指标值的过程；
Multichannel record autocorrelation statistics, accurate well-seismic calibrate means and log data normalization with geology conditions restricting are applied to enhance log model reliability;
采用地质约束的测井归一化处理、多道记录自相关统计、精确的井震标定等手段建立精确的测井约束模型；
One key element to consider is what I call the normalization of data, which provides a single view of different types of data across a city's many domains.
其中一个关键因素就是我提到的规范化数据，它使用一个视图来描述城市主要区域的不同数据类型。
Filtering rules are not the same thing as the normalization rules that aim at reducing data redundancy.
筛选规则与针对减少数据冗余的标准化规则不是一回事。
Normalization focuses only on the meaning of the data, without consideration given to the possible performance requirements of the applications accessing the data.
规范化只关注数据的意义，而没有考虑对于访问数据的应用程序的性能需求。
On the one hand, there is the internal organization of a's data — its normalization and denormalized optimizations, for example.
一方面，是A数据的内部组织——例如，其标准化和取消标准化优化。
The goal in normalization -- to condense the first through fifth "form" of normalization -- is to remove all redundancy in the way data is stored.
标准化的目的 --用第五“范式”来压缩第一范式 --就是除去数据存储方法中的所有冗余。
RDBMSs use a table-based normalization approach to data, and that’s a limited model. Certain data structures cannot be represented without tampering with the data, programs, or both.
RDBMS中使用基于表的数据标准化方法，这是一个很受限的模型，某些非结构化的数据无法表示。
Normalization decisions are finalized in the logical data model resulting in the final normalized representation of entity-to-entity relationships as well as supertype-to-subtype hierarchies.
规范化决定在逻辑数据模型中得以完成，并导致实体-实体关系与超类型-子类型层次关系的最终规范化表示。
Normalization is the formal process of analyzing the data entities needed for an application, and then converting them into a set of well-designed structures.
规范化是分析应用程序所需的数据实体，然后将这些数据实体转化成一组设计良好的结构的一个格式化的过程。
Most relational data design books have pages upon pages of discussion on proper normalization of names and how to avoid design traps with names.
多数关系数据设计书籍都花费相当的篇幅讨论如何正确地规范化姓名和避免姓名带来的陷阱。
The de-normalization causes difficulty on data retrieval, analysis, and quality control.
这种不规范将为数据检索、分析和质量控制增加难度。
This process, called normalization, restructures the data to limit redundancy.
这个过程称为规范化(normalization)，重组数据以限制冗余。
In relational database design, the process of organizing data to minimize redundancy is called normalization.
在关系型数据库设计中，这种组织数据以减少冗余的过程，被称为规范化。
Database normalization is a data design and organization process applied to data structures based on rules that help building relational databases.
数据库规范化是一种基于规则的，施加于数据结构之上的数据设计和组织过程，这种规则有助于建立关系型数据库。
The final ERD (entity relationship model diagram) and system datum dictionary are given through data sheets normalization during logic design and physical design.
在逻辑设计与物理设计过程中通过数据规范化后得出最终的ER模型图并给出系统数据字典。
Data acquisition, normalization, analysis and visualization.
数据采集，标准化，分析和可视化。
The logic framework structured design is consisted of theory analysis of function dependency, relation normalization, transformation from E-R model to relation model and data model normalization.
逻辑结构设计包括函数依赖和关系规范化的理论分析、E - R模型向关系模型的转换和数据模式规范化。
It is refer to normalization of data in building of spatial database of soil and water loss assessing.
在水土流失评价数据库的建立研究中，涉及到数据的标准化问题。
Since the concentration range measured is very wide (0-100%), curve-fitting method is used for obtaining the correlation equation correlating sample's concentration and peak area normalization data.
鉴于相平衡样品的浓度范围宽(0—100%)，所以，定量采用曲线拟合法求得标样浓度与峰面积归一数据的关系方程。
Three important conceptions-function dependence, normalization and dissolution of data scheme-are analysed. Their directive action for design of relational data model is pointed out as well.
避开复杂繁琐的数学推导，分析了关系数据库理论中的函数依赖，数据模式的规范化及其分解这三个重要概念，指出了它们对关系数据模型设计的指导作用。
Research and realizaion of data structure and database design of commerce information processing system is disscused, take warehouse for example, based on normalization theory of data structure.
以数据结构规范化理论为基础，以数据仓库为例，讨论了商务信息处理系统数据结构和数据库结构的合理设计。
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