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covariance相关的网络例句

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与 covariance 相关的网络例句 [注:此内容来源于网络,仅供参考]

Covariance, correlation, linear combinations of random variables, sampling distribution of the mean, confidence intervals for means and proportions.

协方差,相关性,线性组合的随机变量,抽样分布的意思是说,置信区间的手段和比例。

Nowadays, the Eddy Covariance system and the Large Aperture Scintillometer are the main instruments measuring surface fluxes. The former is point observation and can observe hundreds of meters and the latter can observe area average fluxes in the scale of hundreds of meters to ten kilometers.

目前应用较为广泛的通量测量技术有涡动相关仪和大孔径闪烁仪,前者是单点观测,观测范围通常只有几百米;后者近年来得到长足的发展,可以观测从几百米到十几公里尺度上的区域湍流通量。

The algorithms estimate the DOA of the broadband distributed source fron the secondary diagonal elements of the covariance matrices generated from every frequency domain of the received broadband signal s, thus avoiding unwrapping of phases.

该类算法首先将阵列接收的宽带信号变换到频率域,然后对于每个频率形成阵列接收信号协方差阵,最后由该协方差阵的次对角线元素估计宽带分布源的到达角,其主要特点是避免了相位展开。

Singular value decomposition of observability matrix is used to obtain an optimal 2-position alignment, the result is the same as that of covariance analysis.

采用奇异值分解方法对捷联惯导系统静基座下的多位置对准过程中最优位置的选择进行了分析,其结果与协方差分析的结果相同。

For the singular spectrum analysis of time series, a method of constructing covariance matrix by using forth order cumulant is proposed. The method could restrain the Gaossian noise and symmetrical distributed noise mixed with chaotic signals.

对于时间序列的高阶奇异谱分析,提出了一种利用四阶累积量函数构造协方差矩阵的方法,该方法从理论上能有效地抑制叠加在混沌信号中的高斯噪声和对称分布噪声对重构结果的影响。

Under Etropy loss, this new estimate of the covariance matrix is its spectral decomposition estimate.

同时,我们证得:在一些模型中,在Etropy损失下,新估计的风险函数比其谱分解估计,ANOVAE和MINQUE的风险函数小。

Thereinto, for the spectral decomposition estimate of the covariance matrix ,we can gain the risk functions under some losses.

其中,对于观测向量协方差阵的谱分解估计,我们很容易得到它在一些损失下的风险函数。

A reversible Markov process as a chemical polymerization model where a gelation transition exists is presented. The stationary distribution, partition function and expression of covariance of this model are obtained.

以存在凝胶化现象的高分子反应模型为背景,定义了高分子反应所对应的可逆Markov过程,给出了过程的稳定分布及配分函数,推导出了分子间协方差的表达式。

In this dissertation , the methods of prediction and parameters\' estimation based on stationary multivariate autoregressive models AR(p are studied systematically. Some properties of these methods are formulized.In the first part, it introduce some basal conceptions about multidimensional stationary time series, contained the estimation and property of mean vector and auto-covariance function. Then the stable condition of multidimensional AR models are discussed.

本文主要研究了多维平稳序列自回归模型AR的参数估计及其相关的统计性质,具体内容如下:第一部分,介绍了多维平稳时间序列及其均值向量和协方差阵函数的概念,并引入了多维AR模型及其数字特征,在此基础上给出了模型的平稳性条件。

Secondly, when kalman filter has reached steady state its error covariance will have a very small stationary value, namely filter dropping off'. Thirdly, the traditional kalman filter cannot adjust its filter parameters with statistic characteristic of the noise. To overcome the deficiency of kalman filter, an SVD-based adaptive kalman filter is put forward in the paper. The filter restrains the filter divergence by matrix singular value decomposition. The eigenvalues and eigenvectors of the matrix are insensitive to tiny change of matrix element and acceptable error.

然而,传统的卡尔曼滤波器存在以下问题:问题一,因噪声统计特性估计不准确和计算机舍入误差引起的滤波发散现象;问题二,在卡尔曼滤波器达到稳态时,其误差方差阵将饱和使其对信号的突变变得不敏感,问题三,传统的卡尔曼滤波器对滤波参数无自适应能力,不能随着噪声统计特性的改变而调整自身的滤波参数。

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