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数据相关性的英文

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"数据相关性"怎么读用"数据相关性"造句

英文翻译手机手机版

  • data dependence
  • data dependency

例句与用法

  • We also describe a dynamic method of detecting data dependence
    同时,我们还提出了判断数据相关性的动态测试。
  • After the information ray - space was described , the data correlations and distribution characteristics were discussed
    基于光线空间描述,讨论了其数据相关性和数据分布特性。
  • We can deal with the programs that contain some input variables , the programs with control structures and unexecutable paths . with our method more information will be acquired and the accuracy of the analysis will be improved
    数据相关性的静态测试可以精确处理数组下标表达式为线性表达式的情况,而且还可以精确求解数组下标中含有输入变量的情况。
  • Therefore , it is generally better to separate code on which persisted data dependencies rely such as user - defined types and indexes using user - defined functions from code that does not have such persisted data dependencies
    因此,通常将持久化数据相关性依赖(例如使用用户定义函数的用户定义类型和索引)的代码与没有这种持久化数据相关性的代码分开更好。
  • In static analysis , we generate the control flow graph of the sequential program and convert the graph to an extended finite state machine ( efsm ) . by analyzing the paths of the efsm , we can find whether there is data dependence in the program or not
    数据相关性的静态测试中,我们首先生成程序的流程图,在遍历流程图的同时生成这个程序的扩展有限状态机( efsm ) ,然后调用路径分析工具对efsm的路径进行分析。
  • The bottleneck of performance include : the ability of handling data ; the ability of transfering data , if the necessary data is not in local memory , the processor cant work ; the dependency of data , parallel handling the data which be known beforehand
    以往的dsp和媒体处理器缺乏mpeg2编码解码的实时处理能力,性能瓶颈主要包括:数据处理能力;数据传输能力,当所需数据不在本地内存时,处理器无法进行任何操作;数据相关性,预知数据并行处理。
  • The main content of this paper is compress arithmetic of multi - spectral image , and the implement with fpga . in the phase of preprocess , the paper analyses the characteristics of multi - spectral image , classifies data redundancy to two classes : spatial - redundancy and spectral - redundancy , afterwards , eliminates these data redundancy with different forecast models
    在预处理阶段,本论文分析了多光谱图像的数据特点,将多光谱图像数据中存在的数据冗余分为两大类:空间冗余和谱间冗余,再针对每种冗余使用相应的预测模型消除数据相关性
  • Now , there are four evaluation methods in this field , every method has its advantages and shortages and most of them are established based on highway . high weight communication , great loads channelized traffic and high speed is the expressway ' s feature , there is great difference in the development law between highway and expressway . we will get some unfitness result by using those evaluation methods to evaluate expressway
    目前国内外常用的四类路面使用性能评价方法中回归法评价结果与实测数据相关性不太理想,系统分析法客观性不强,灰色理论法存在一定的主观经验性,其它一些方法还处于研究阶段;而且这些方法都是基于普通公路建立,高速公路具有交通量大、汽车轴载重、交通渠化和行车速度高等特点,路面使用性能的特点和发展变化规律与普通公路存在较大差异。
  • The dynamic distributed principia on the simulation module are given , as well as the dynamic analyses arithmetic on the load of the servers . the arithmetic which to test the data pertinence of the simulation module which driven by the data source is put forward . the dissertation also designs an efficient distributed arithmetic on the simulation module the concept of xml template is put forward to realize the save format and the backward - compatibility of visualize edit interface system
    研究过程中,作者确立了松散耦合分布式的系统架构;给出了仿真模块动态分布式的原则和服务器负载状况动态分析算法,提出了数据源驱动的仿真模块数据相关性检测的算法,设计了简单而有效的仿真模块动态分布式算法;提出了xml模版的概念,实现了存储格式和可视化编辑界面系统的向后兼容的问题;使用soap实现异构仿真组件的远程调用与数据交换;提出仿真容器的模型来简化异构组件间通信对二次开发造成的负担;建立了仿真模块自适应检测的机制,达到仿真算法系统的通用性。
  • Abstract by setting up a network model of data aggregation and using a bit - hop metric to quantify energy costs in wireless sensor networks , we formally analyze the problem of area - based data aggregation and obtain that data aggregation will definitely be energy efficient when the relative difference between the average lengths of the two shortest paths , which are from source sensor nodes to the sink and to the aggregation node respectively , is not less than the ratio of data correlation to the number of source sensor nodes
    摘要通过抽象出无线传感器网络中区域数据回传的网络模型,定量研究了区域数据聚合的节能条件,证明了先聚合再回传比直接进行数据回传所节省的相对路径长度,如果大于等于数据相关性与源节点个数的比值时,区域数据聚合一定可以节省能耗,并进一步给出了当数据聚合点在网络的不同位置,或数据的空间相关性不同时,区域数据聚合的节能条件。
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