- 更多网络例句与双变量分布相关的网络例句 [注:此内容来源于网络,仅供参考]
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In addition, there will be bimodal distribution for time series if there is a linear trend, but it doesn't change the probability distribution of differences of scalars.
同时,也发现,线性趋势的存在会使原变量的概率分布出现双峰,但是不会影响变量差的概率分布。
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In this paper, considering inter- scale dependency, we introduced a bivariate probability distribution model.
该文考虑到小波系数层间相关性,引入双变量概率分布模型。
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The statistics of the contourlet coefficients of natural images in detail and model contourlet coefficients using non-Gaussian bivariate distribution that captures their interscale dependencies are studied.
详细分析了图像contourlet系数的统计特性,并利用非高斯双变量分布对系数层间相关性进行建模。
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To improve the performance of image-denoising methods, a locally adaptive denoising algorithm was presented. The new algorithm assumed the statistical dependence among wavelet coefficients. First, a bivariate probability distribution model was introduced to model the statistics of wavelet coefficients, and corresponding nonlinear threshold function was derived from the model using the Bayesian estimation theory.
由于图像小波系数存在很大的层间相关性,引入双变量概率分布模型,基于贝叶斯估计理论,得到了相应的非线性阈值函数;基于层内局域方差估计,利用该收缩函数得到一种局域自适应的图像去噪算法。
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Consider the dependencies between the coefficients and their parents, a non-Gaussian bivariate distribution is given, and corresponding nonlinear threshold function is derived from the model using Bayesian estimation theory. According to non-subsampled Contourlet transform and bivariate threshold function, a novel Non-Subsampled Contourlet Transform based on Bivariate threshold function for image denoising is proposed. This scheme achieves enhanced estimation results for images that are corrupted with additive Gaussian noise over a wide range of noise variance.
该文依据非下采样Contourlet分解系数与其父系数之间的相关性,给出非高斯双变量分布,对该模型应用Bayes估值理论推导得到相应的非线性双变量阈值函数,综合非下采样Contourlet分解和双变量阈值函数,提出一种基于双变量阈值的非下采样Contourlet变换图像去噪方法。
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In this paper, we study the convergences and the growth of bi-random Dirichlet series by the strong law of large numbers for independent and non-equally distributed random variables, and obtain some new result.
利用独立不同分布的随机变量序列的强大数定律研究了双随机狄里克莱级数的收敛性和增长性,得到了一些新的结果。
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In this paper, we study the convergences and the growth of bi-random Dirichlet series by the strong law of large number s for independent and non-equally distributed random variables, and obtain some new result.
利用独立不同分布的随机变量序列的强大数定律研究了双随机狄里克莱级数的收敛性和增长性,得到了一些新的结果。
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In chapter 2, the oscillation of a class of nonlinear hyperbolic equations with continuous distributed deviating arguments is studied.
第二章研究了一类带连续分布时滞变量的非线性双曲方程的振动性。
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In this paper, taking one 1900t/h supercritical pressure once—through boiler installed in East boiler company as subject investigated, analyzing the structure and characteristic of unit, from the mechanism of units, based on the law of quality conservation, energy conservation and momentum conservation, having Lagrange fluid particle tracing idea in hydrodynamics field application in analyzing of unit operational characteristic, author build up the nonlinear distributed parameter general dynamic mathematical model of single-phase heating surface or diphase heating surface in the steam-water system for supercritical pressure once—through boiler, which is suitable numerical calculation and simulation for large scale disturbance and full working conditions change, and enough materializing distributed characteristic of thermodynamic parameter in process and time lag characteristic of energy transportation in tache. The transient responses curve of the system main variables under several disturbance are computed by Computer Simulation for the model, and theoretical analysis shows that the simulation results are reasonable.
本文以东方锅炉集团公司的一台1900 t /h超临界压力直流锅炉为研究对象,在分析机组结构和特性的基础上,从机组的工作机理出发,以质量、能量、动量守恒定律为依据,将流体力学领域中的Lagrange流体质点追踪思想用于机组运行特性的分析上,建立了适用于超临界压力直流锅炉汽水系统单相、双相受热面的非线性分布参数通用动态数学模型,该模型适合于大扰动全工况变化的数值仿真计算,充分体现了过程热力参数的分布特性和环节中能量输送过程的时滞特性,并对模型通过计算机仿真得出各种扰动下系统主要变量的响应曲线,从理论上分析了仿真结果的合理性。
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MR images was analyzed include tumor shape,margin, internal enhancement characteristics,distribution,and time-signal intensity curves,maximam enhancement ratio,early enhancement ratio and so on.The ADCs of lesions were calculated on ADC maps.Univariate and multivariate analysis of MR imaging data were performed to find the strongest discriminators and the Logestic regression model was established to predict the probabilities for malignancy.
由放射科医生采用双盲法阅片,根据乳腺MR影像报告及数据系统(BI-RADS MRI),将病变按照不同形态学表现分为肿块和非肿块性病变两组,分析形态学表现(形状、边缘、分布特征、内部增强特征)、血流动力学表现(时间-信号强度曲线类型、最大增强率、达峰时间、早期增强率),并结合ADC值,应用SPSS15.0软件进行单变量及多变量分析,挖掘有意义恶性征象,建立回归模型,计算其敏感性、特异性、准确性、阳性预测值和阴性预测值。
- 更多网络解释与双变量分布相关的网络解释 [注:此内容来源于网络,仅供参考]
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bivariate distribution:双变量分布
biuret reaction 缩二脲反应 | bivariate distribution 双变量分布 | bivariate population 双变量总体
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point bivariate distribution:点二变量分布;点二变量分配
点双数列相关 point biserial correlation | 点二变量分布;点二变量分配 point bivariate distribution | 点密度 point density
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Bivariate normal distribution:双变量正态分布
线性相关(linear correlation)又称简单相关(simple correlation),用于双变量正态分布(bivariate normal distribution)资料. 其性质可由散点图直观的说明. 1. 意义:相关(correlation coefficient)又称Pearson积差相关系数,用来说明具有直线关系的两变量间相关的密切程度与相关方向.
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bivariate population:双变量总体
bivariate distribution 双变量分布 | bivariate population 双变量总体 | bivoltine 二化性
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bivariate discrete distribution:二元离散分布
bivariate density function 二元密度函数 | bivariate discrete distribution 二元离散分布 | bivariate distribution 二维分布,二元分布,双变量分布
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bivariate normal density:双变量正态分布
dirac delta function:脉冲函数,狄克拉函数. | zero-mean,unit-variance,univariate normal density:0均值,1方差,单变量正态分布. | bivariate normal density:双变量正态分布
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zero-mean,unit-variance,univariate normal density:0:均值,1方差,单变量正态分布
dirac delta function:脉冲函数,狄克拉函数. | zero-mean,unit-variance,univariate normal density:0均值,1方差,单变量正态分布. | bivariate normal density:双变量正态分布
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Biariate normal population:双变量正态总体
Biariate normal distribution, 双变量正态分布 | Biariate normal population, 双变量正态总体 | Biweight interal, 双权区间
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bivariate normal surface:双变量正态曲面
bivariate normal distribution 双变量正态分布 | bivariate normal surface 双变量正态曲面 | block 配伍组,区组
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bivariate correlation:双变量相关
bivariate analysis 双变量分析 | bivariate correlation 双变量相关 | bivariate distribution 二元分布