By the geometric probability model, the intuitionistic method is provided for the marginal density function and conditional probability density function. 利用几何概型得出均匀分布的边缘密度函数和条件概率密度函数的直观求法。
Only when Class-conditional-probability density is known, the theory can be used. 但这一理论的应用是以己知类条件概率密度为前提。
Maximum Conditional Probability Density Estimation of Extended Networks and Its Estimation Formulae for Variance Components 扩建网极大条件密度估计及其方差分量估计公式
At the end of the paper, with the help of the relation between brink probability density conditional probability density and associated probability density, the probability model of the index formulae is discussed. 并利用边缘概率密度、条件概率密度和联合概率密度之间的关系,对指标公式的概率模型做了一定的探讨。
This paper derives the formulae of maximum conditional probability density estimation used for extended control network suitable for one, and sum up composition method of the equivalent normal equation and the coefficient matrix of unknowns. 本文作者从整体平差原理出发,推导了Qx^′2奇异时扩建网的极大条件密度估计公式,总结了等价法方程和参数协因数阵的组成规律。
A conditional probability density function of wave period, assuming wave height, is derived on the basis of normally distributed waves. 在海浪波面高度为正态分布的假定下,导出一种以给定波高为条件的条件周期概率密度函数。
Suppositive conditions are given of calculating probability of surviving by using the whole probability formula. The general expression of the solution and the integral equation are deduced which satisfies conditional probability density function. 给出利用全概率公式计算船舶破损后残存概率的假设条件,并推导条件概率密度函数所满足的积分方程及解的一般表达式。
Based on the integral equation method, which is presented by Madsen and so on, the conditional upcrossing rate, the joint upcrossing rate and the first-passage time probability density are obtained by use of single-point FORM method for first-passage of structures. 本文在Madsen等提出的积分方程方法基础上,采用单点FORM方法计算结构首次穿越问题中的条件穿越率、联合穿越率及首次穿越时间概率密度。
The primary of Bayesian estimation is to deduce the conditional distribution function of unknown variables on the data, which is also called posterior probability density function ( PPDF). 它是根据测量的数据推导未知变量的条件分布函数,也就是后验概率密度函数,而热传导反问题的数值解就是后验概率密度函数的数学期望。
Precision Estimation of Maximum Conditional Probability Density Estimation for Extended Control Networks when Q_x_2~ ′ Being Rank Defect 协因数阵秩亏时扩建网极大条件密度估计的精度
The conditional probability density function of the state of a stochastic dynamic system seems to be the complete solution to the filtering problem. 随机动态系统状态的条件概率密度函数可以说是滤波问题的完全解[3]。
Kernel density estimation is used to estimate the class conditional probability density of differencing image, and is combined with weighted MRF to classify the differencing image. Finally, the change detection map is generated. 首先采用核密度估计的方法估计差异图像的类条件概率密度,再结合变权MRF模型进行差异图像的分类,生成变化检测结果图。
In the algorithm, the class conditional probability density function was defined as the reciprocal of the distance between sample X and the cluster center. 在概率聚类算法中,类条件概率密度函数定义为样本X到该类聚类中心之间距离的倒数。
Using assumed explained variable condition, applying the maximum entropy principle and with the condition probability distribution complying with that of sample data and prior distribution, the author finally estimates an optimal conditional probability density of the LGD. 利用假定的解释变量条件,应用最大熵原理,并要求所估计的条件概率分布一致于样本数据和先验分布,最终对违约损失率估计出最佳的条件概率密度。