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准确的离散
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  “准确的离散”译为未确定词的双语例句
     In this paper, two local fitting and differentiation (the incremental polynomial method and the Chebyshev polynomial method) in numerical differentiation for non-accurate discrete data are described, and so are the applications in data processing of fatigue crack growth rate tests and in life prediction.
     本文介绍了对非准确的离散数据进行数值微分的两种“局部拟合微分法”(递增多项式法和Chebyshev多项式法)及其在疲劳裂纹扩展速率实验数据处理与寿命予测等方面的应用。
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  相似匹配句对
     Practical application showes that the dispersing method possesses advantages of rapidily and accuracy.
     实践应用表明,该方法离散快速、准确
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     From the famous discrete W.
     从离散型W.
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     An Exact Number
     准确数字
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     Accuracy and Interest
     准确·趣味
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     insist nicety;
     强化准确;
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  accurate discrete
Hence, to convert them into an accurate discrete representation, the sampling rate should be infinitely high.
      
The second order accurate discrete equations cannot be solved this way because they lack sufficient numerical diffusion.
      


In this paper, two local fitting and differentiation (the incremental polynomial method and the Chebyshev polynomial method) in numerical differentiation for non-accurate discrete data are described, and so are the applications in data processing of fatigue crack growth rate tests and in life prediction.

本文介绍了对非准确的离散数据进行数值微分的两种“局部拟合微分法”(递增多项式法和Chebyshev多项式法)及其在疲劳裂纹扩展速率实验数据处理与寿命予测等方面的应用。

It is well known that,when a priori values aDd noise statistics are hot given, maximum likelihoodmethods are not sufficiently effective in estimating the frequently CDcountercd big errors of measurementsof night state. To improve such effectiveness,this paper presentS an emcient discrete-time maximum likelihood method for parameter estimation. Compared with the maximum lilieliliood method used by manynight test groups,the author,s method appears to be better in the following respects:(l)High accuracy in estimated...

It is well known that,when a priori values aDd noise statistics are hot given, maximum likelihoodmethods are not sufficiently effective in estimating the frequently CDcountercd big errors of measurementsof night state. To improve such effectiveness,this paper presentS an emcient discrete-time maximum likelihood method for parameter estimation. Compared with the maximum lilieliliood method used by manynight test groups,the author,s method appears to be better in the following respects:(l)High accuracy in estimated results.The computation of scnsitivity matrix with ordinary maximum likelihood method ~ins such big errors that it gives inaccurate results of parameter estimation.The present paper develops an accurate d-iscrctc--time model of motion of an aircraft to get exact expression ofsensitivity matals. Thus the accuracy of estimation resultS is increased.(2 Good convergenCy.By using the new method. the covatiances of process noises are reduCed toass than 1/8.But in the ordinary maximum likelihood method process noises are not considered.Fndbermore. the new approach can g

本文提出了一种有效的离散系统参数估计的极大似然方法,并书其成功地应用于飞行数据处理中.为了保证飞行状态测量偏差估计的精度,本文提出了飞机运动准确离散化模型,利用积分求和法使系统噪声大大减少;并利用分级估计法大大提高了计算效率.数字仿真和对我国几种类型飞机的飞行数据实际计算表明,这一方法能够准确地估计出飞行状态和仪器误差,对不同的初值和噪声统计特性均能得到一致的结果.

In this paper we give a model of single populations growth,i.e.a generalized Logistic model with Dirac comb.Then we get its exact discrete form.At last we discuss the dynamics of the discrete model.

本文给出了一类种群增长模型——带有Dirac梳的广义Logistic模型,然后对该模型进行了准确的离散化,并分析了离散后模型的动力学。

 
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