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a random variable
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  随机变量
     To a random variable X~N(μ,σ 2),the effect of σ is demonstrated by using two methods on MATLAB software platform.
     对于随机变量X~N(μ ,σ2 ) ,在MATLAB软件平台上 ,用两种方法演示了σ对X取值的影响 .
短句来源
     Assuming that there are k parent populations(G_1,G_2,…,G_k)and that F_i,whose probability density is P_i,is a random variable from the parent population G_i,we can derive both the covariance matrix W in parent population and the covariance matrix B between parent popula- tions in the light of multivariate statistical analysis theory.
     设有 k 个母体 G_1,G_2,…,G_k,F_i 为来自母体 G_i 的随机变量,P_i 为其概率密度,根据多元统计分析理论,可以求出母体内的协方差阵 W 和各母体间的协方差阵 B。
短句来源
     The statistic properties of a random variable sequence on Z_9 gained by two random variable sequences on Z_3
     由域Z_3上随机变量序列构造的剩余类环Z_9上随机变量序列的统计性质分析
     This paper shows that the stochastic process,on condition that ξ(t)=acos(t+Θ)(a is a positive constant,Θ is a random variable ) is not stationary, and gives a sufficient condition for this type of stochastic processes to be stationary, that is getting a stationary subclass of this kind of stochastic processes.
     举出随机过程 ξ(t) =acos(t+Θ) (a为正的常数 ,Θ为一随机变量 )为非平稳过程的例子 ,给出这类随机过程为平稳的一个充分条件 ,即得出这类随机过程的一个平稳子类
短句来源
     Records about a Random Variable Distribution Function Definition Note
     关于随机变量分布函数定义的一点注记
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  “a random variable”译为未确定词的双语例句
     Let X_(1,n),…, X_(N,n) be a segment of an infinite sequence of exchangeable random variables, X_(1,n)~*≤…≤X_(N,n)~* be its order statistics, and N=N(n) be a random variable which is independently distributed of the X's, n=1, 2,….
     设X_(1,n) …,X_(N,n)是可换r. V. 无穷序列的一段,X_(1,n)~*≤…≤X_(N,n)~*为其顺序统计量,N=N(n)是与这些X(1,N)独立的正整值r.
短句来源
     Give the Distribution Function of a Random Variable Utilizing its Moments
     随机变量的分布函数及其计算
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     In atmosphere, the spectrum scale is very wide, so in atmospheric boundary layer the magnitude ΦT(K0) or G2T measured by acoustic radar is a random variable obeying the logarithmic normal distribution.
     由于大气中谱的尺度很宽,在边界层大气中,用声雷达测得的Φ_T(K_0)或C_T~2是一个随机量,具有正偏态分布的特性,并满足对数正态分布。
短句来源
     Assume that Ⅹ is a random variable whose density function f(x, θ) is iudexed by the parameter θ, and θ is unknown.
     设有总体X具有概率密度或概率分布列f(x,θ),θ未知,θ∈(?)
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     Polynomial Approximation of A Random Variable
     随机变量的多项式最佳均方误差逼近
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  相似匹配句对
     Wind load is a random variable.
     风荷载是一种随机荷载.
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     A kind of discrete random variable
     一类离散型随机变量
短句来源
     ON RANDOM
     论随机性
短句来源
     On Selection of the Variable
     关于自变量的选择
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     Random Sampling
     随机抽样
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  a random variable
The duration of every job is a random variable distributed by a given law.
      
The developed methods are based on the modified normal distribution function of a random variable.
      
The amount of work required for servicing an incoming customer (workload) is a random variable with an arbitrary distribution function.
      
The excess 1/f noise in a random lattice with bond resistances r~exp(-λx), where x is a random variable and λ?1, is studied theoretically.
      
The zero temperature phase diagram for ultracold bosons in a random 1D potential is obtained through a site decoupling mean-field scheme performed over a Bose-Hubbard (BH) Hamiltonian, whose hopping term is considered as a random variable.
      
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The magnitude of temperature fluctuation spectrum ΦT(K0) or temperature structure coefficient G2T can be directly measured by acoustic radar. In atmosphere, the spectrum scale is very wide, so in atmospheric boundary layer the magnitude ΦT(K0) or G2T measured by acoustic radar is a random variable obeying the logarithmic normal distribution.We analysed the frequency spectra of ΦT(K0) and found that in the frequency range of 10-3-3 × 10-3 c/s there is a maximum value vange of energy. Between the maximum...

The magnitude of temperature fluctuation spectrum ΦT(K0) or temperature structure coefficient G2T can be directly measured by acoustic radar. In atmosphere, the spectrum scale is very wide, so in atmospheric boundary layer the magnitude ΦT(K0) or G2T measured by acoustic radar is a random variable obeying the logarithmic normal distribution.We analysed the frequency spectra of ΦT(K0) and found that in the frequency range of 10-3-3 × 10-3 c/s there is a maximum value vange of energy. Between the maximum value range and high-frequency range exists a sharp transitional band of energy. At past years some meteorologists usually considered that there is a gap in the meso-scale range of spectra. In this articale, it is shown that at meso-scale range, whenever in stable or unstable conditions there is a cyclic activity of time scale from several minites to more ten minites and it makes a great contribution to the energy. This phenomena may be of importance for the theoritical research of the atmospheric turbulence. Since in the atmosphere the spectral range is very wide, we must select correctly the length of mean time in the measurement of meteorological elements or other physical parameters to obtain their stable means.

声雷达可以直接测量温度脉动谱Φ_T(K_0)或温度结构系数C_T~2值。由于大气中谱的尺度很宽,在边界层大气中,用声雷达测得的Φ_T(K_0)或C_T~2是一个随机量,具有正偏态分布的特性,并满足对数正态分布。 从Φ_T(K_0)的频谱分析中得到,在频率为10~(-3)—3×10~(-3)秒~(-1)的范围内,存在着一个能量的峰值区,峰值和高频之间,能量的过渡带很陡。过去一般认为中尺度范围是大气谱段中能量的低值区。本文的分析发现,在中尺度范围内,无论在稳定或不稳定层结,经常存在着几分钟到十几分钟的周期活动,并对能量产生较大的贡献。这对今后大气湍流理论的研究,是一个值得注意的问题。此外,由于大气中谱尺度很宽,必须正确地选取气象要素或其它物理量的平均时间,才能获得稳定的气象要素的平均值。

Let X(t) be a stationary ergodic random signal, then its power spectrum density at frequency f isWhen we find the power spectrum density by means of the power spectrum density analyzer, the time of integration T. the filter bandwidth B and the RC-time constant of the integrator are not ideal, therefore the output of the analyzer is a random variable. This paper derives the formula used to calculate the influence of the RC-time constant to the output of the analyzer. The output of the analyzer is a biased...

Let X(t) be a stationary ergodic random signal, then its power spectrum density at frequency f isWhen we find the power spectrum density by means of the power spectrum density analyzer, the time of integration T. the filter bandwidth B and the RC-time constant of the integrator are not ideal, therefore the output of the analyzer is a random variable. This paper derives the formula used to calculate the influence of the RC-time constant to the output of the analyzer. The output of the analyzer is a biased estimate of the real power spectrum density. When T≥4RC, the relative deviation may be less than 2%. The RC-time constant has no significant influence to the statistical error, but the relative deviation may be more than 20 db when the time of integration T is too short. The relative accuracy may be adjusted by the standard Sine signal. The-oretical results presented in this paper are examined to be coincident with the experimental ones.

设x(t)是平稳的,各态历经的随机过程,则在频率f的功率谱密度W(f)为在用电子模拟设备求功率谱密度时,积分时间T、带宽B及积分器的积分常数都不是理想的,从而模拟设备一次处理的结果是一个随机变量。本文分析了积分器的时间常数的影响。分析表明:由于积分器的时间常数RC的存在,模拟设备输出的功率谱密度是真功率谱密度的有偏估计,当T≥4RC时,其相对偏差可小于2%。分析表明:RC对统计误差基本上没有影响。但积分时间如选得过短,将可能产生多达20db的相对偏差。用标定的正弦信号可判定所选的积分时间是否合适。文中附有试验的记录曲线,它说明试验与理论分析是一致的。

eLet X be a random variable with exponential distribution whose density function is(?) where-∞<μ<∞,O<σ<+∞,bothh and σ being unknown.This paper gives a new estimator of σ.(?)_2=(?)where (?)n is the sample size,r is the number of terms retained when censored on the right,and x_((j)) denotes the i-th order statistic,i=1,…,r.In this paper it is shown that for loss function L((?),or) =((?)-1) ~2,the risk of (?)_2 is much smaller than that of the best affine invariant estimation (?)_1=1/r(?); hence an improvement....

eLet X be a random variable with exponential distribution whose density function is(?) where-∞<μ<∞,O<σ<+∞,bothh and σ being unknown.This paper gives a new estimator of σ.(?)_2=(?)where (?)n is the sample size,r is the number of terms retained when censored on the right,and x_((j)) denotes the i-th order statistic,i=1,…,r.In this paper it is shown that for loss function L((?),or) =((?)-1) ~2,the risk of (?)_2 is much smaller than that of the best affine invariant estimation (?)_1=1/r(?); hence an improvement.

设 X 是具有指数分布的随机变量,其密度函数为p(x)=(?)其中-∞<μ<+∞,0<σ<+∞,μ和σ均未知。本文给出了σ的一个新的估计(?)+(n-r)x_((r))-nx_((1) )]·f(?)(y),此处y=(?),f(?)(y)=(?)n 是子样容量,r 是截尾数,x_((i))表示第 i 个顺序统计量(i=1,2,…,r)。文中证明了(?)关于损失函数 L((?),σ)=(((?)/σ)-1) ~2比最佳仿射同变估计(?)=1/r[(?)x_((i))+(n-r)x_((r))-nx_((1) )]处处有较小的风险,因此是一个改进。

 
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