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zero mean Gaussian model 零均值高斯模型
W is a zero mean white noise source. W是一个零均值的白噪声源。
The diffusion of radio-nuclides in atmosphere was studied on the basis of Gaussian Model. 摘要在高斯烟羽模型的基础上，对核事故中放射性云团在大气中的扩散规律进行了研究。
In this study, those remaining effects are treated asstochastic noise and are assumed white Caussian distributed with zero mean. 在这项研究中,那些未被考虑的各影响因素被作为随时噪声加以处理,并假设其具有零均值白高斯分布。
Two consecutive frames was subtracted to pick up background pixel in this method, then the Gaussian model of every pixel was built. 该方法基于帧间差分法检测出帧中的背景像素点后，再确立每个点的高斯模型，最后运用背景差分准确检测出场景中的运动目标。
In this example for that X is a zero mean uniform R.V, Y is a zero mean uniform R.V, U is the difference of R.V.X, Y, and V is the product of R.V. 本文以甲变数为均匀随机变数，乙变数为均匀随机变数，丙变数为甲乙随机变数之差，及丁变数为甲乙随机变数之积的情况下，图示验证二维随机变数联合机率之特性。
We calculate the cross-correlation function (CCF) for the light curves in 25-55 and 110-300 keV bands and derive the spectral lag by fitting the CCF with the Gaussian model. 我们计算了25-55和110-300kev能段的互相关函数(COF)，并通过高斯模型拟合CCF得到光谱时滞。
Long-term diffusion model of atmospheric pollutant (ISCLT3) called regulatory model is a kind of Gaussian model recommended by U.S. Environmental Protection Agency. 大气污染长期扩散模型(ISCLT3)是高斯模型的一种,是美国环境保护署强制推荐的大气污染扩散模型,并称为法规模型;
In this example for that X is the product of zero mean uniform R.V.Urn0, Y is a zero mean uniform R.V, U is the cosine of product of R.V.X, Y, and V is the difference of R.V. 本文以甲变数为均匀随机变数之积，乙变数为均匀随机变数，丙变数为甲乙随机变数积之馀弦，及丁变数为甲乙随机变数之的差情况下，图示验证二维随机变数联合机率之特性。
Presented here is the calculation of the diffusion of radionuclides from the Daya Bay Nuclear Power Plant under normal operation on the basis of Gaussian model. 摘要以高斯烟羽模型为基础对大亚湾核电站正常运行时所释放的放射性核素在大气中的扩散进行模拟计算。
In this example for that X is a zero mean uniform R.V, Y is the product of zero mean uniform R.V.Urn0, U is the sum of R.V.X, Y, and V is the cosine of product of R.V. 本文以甲变数为均匀随机变数，乙变数为均匀随机变数之积，丙变数为甲乙随机变数之和，及丁变数为甲乙随机变数积之馀弦的情况下，图示验证二维随机变数联合机率之特性。
In this example for that X is the sum of zero mean uniform R.V.Urn0, Y is the cosine of zero mean uniform R.V.Urn0, U is the product of R.V.X, Y, and V is the sum of R.V. 本文以甲变数为均匀随机变数之和，乙变数为均匀随机变数之馀弦，丙变数为甲乙随机变数之积，及丁变数为甲乙随机变数之和的情况下，图示验证二维随机变数联合机率之特性。
In this example for that X is a zero mean normal R.V, Y is the product of zero mean uniform R.V.Urn0, U is the even exponential of sum of R.V.X, Y, and V is the product of R.V. 本文以甲变数为均匀随机变数，乙变数为均匀随机变数之积，丙变数为甲乙随机变数和之偶指数函数，及丁变数为甲乙随机变数之积的情况下，图示验证二维随机变数联合机率之特性。
In this example for that X is the sum of zero mean uniform R.V.Urn0, Y is a zero mean uniform R.V, U is the product of R.V.X, Y, and V is the difference of R.V. 本文以甲变数为均匀随机变数之和，乙变数为均匀随机变数，丙变数为甲乙随机变数之积，及丁变数为甲乙随机变数之的差情况下，图示验证二维随机变数联合机率之特性。
In this example for that X is a zero mean normal R.V, Y is the cosine of zero mean uniform R.V.Urn0, U is the even exponential of sum of R.V.X, Y, and V is the difference of R.V. 本文以甲变数为均匀随机变数，乙变数为均匀随机变数之馀弦，丙变数为甲乙随机变数和之偶指数函数，及丁变数为甲乙随机变数之的差情况下，图示验证二维随机变数联合机率之特性。
The comparisons between the simulated results of two models and experiments show that double ellipsoidal model is better than Gaussian model on three-dimensional analysis. 两种模型的仿真结果与工艺试验结果比较表明，双椭球形热源模型比高斯热源模型更适合双丝焊的三维有限元分析。
The vehicle emission dispersion models can be classified into Gaussian model,empirical model,numerical simulation model and box model. 机动车排放污染扩散模式可分为高斯模式、经验模式、数值模拟模式和箱式模式。
The Gaussian model is used to normalize the sub-characters of different images.Finally, the texture similarity between the querying image and other images is computed by the Euclidean distance. 针对特征向量进行高斯归一化，利用欧氏距离计算不同图像间的纹理相似度。
A weighed double Gaussian model is proposed to estimate super-Gaussian and sub-Gaussian probability density.In the framework of natural gradient, model parameter is calculated online by kurtosis. 该算法用加权双高斯模型估计超高斯与亚高斯信源分布，在自然梯度框架下，依据峭度实现模型参数自适应。
In this example for that X is the cosine of zero mean uniform R.V.Urn0, Y is theGaussian of zero mean uniform R.V.Urn0, U is the sum of R.V.X, Y, and V is the cosine of product of R.V. 本文以甲变数为均匀随机变数之馀弦，乙变数为均匀随机变数之高斯函数，丙变数为甲乙随机变数之和，及丁变数为甲乙随机变数积之馀弦的情况下，图示验证二维随机变数联合机率之特性。

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