先验概率

The samples actually observed. In contrast Bayesian methods view the parameters as random variables having some known a priori distribution.

与此不同的是，贝叶斯估计则把待估计的参数看成是符合某种先验概率分布的随机变量。

Through the modification of the present model, the uniform distribution was supplanted by the original image distribution and a priori probability updating was added in order to approach the realistic distribution.

通过对已有的模型进行改进，将原始信号分布代替均匀分布并增加了先验概率的迭代，使得分布情况更符合实际。

Gaussian mixture model calculated a priori probability and the probability of post-mortem procedures, using a large matrix computation, g...

计算高斯混合模型先验概率和后验概率的程序，采用大矩阵运算，大大提高了运行速度。

Gaussian mixture model calculated a priori probability and the probability of post-mortem procedures, using a large matrix computation, greatly improved speed.

计算高斯混合模型先验概率和后验概率的程序，采用大矩阵运算，大大提高了运行速度。

The second step is to evaluate for BN, decide prior probability and conditional probability.

再为贝叶斯网络赋值，确定先验概率和条件概率。

In this paper, a speckle reduction method for SAR images based on Dual Tree Complex Wavelet Transform is proposed. It first presumes the probability distribution function for complex wavelet coefficients of the original nature image, and then applies MAP theory to estimate coefficients from the noisy wavelet coefficients. Filtered image can be derived after inversed DTCWT.

该方法首先对无噪声污染图像的复数小波系数的统计概率分布进行建模；然后利用此先验概率模型，采用最大后验概率方法从含噪小波系数中估计出无噪声污染的小波系数：最后经重构得到滤波后的图像。

Through this model, which could make full use of the given prior information as the constraints of maximum likelihood estimation and based on Lagrange function, the calculation problem of fault prior probabilities was transformed to non-constrained optimization problem.

该模型以相关的先验信息作为最大概率估计的约束条件，并通过拉格朗日函数，将故障先验概率估算问题转化成无约束优化问题。

The prior probability can be estimated by using the equivalence of the Markov random fields and the Gibbs Distribution.

先验概率可以根据马尔可夫随机场和吉布斯分布的等效性，用GD的概率估计。

First, an extended rough set model based on valued tolerance relation and prior probability obtained out of incomplete information system is founded. Then, as a part of the model, the attribute reduction of incomplete information system and the corresponding discernibility matrix are proposed, and the attribute reduction is obtained by the normal form transform.

作者首先从扩展粗集理论适应范围的角度出发，引入信息系统对象的先验概率，结合量化相容关系的思想，提出基于先验概率的相容关系模型，然后以该模型为基础研究了不完备信息系统的属性约简，通过严格的数学证明，得到基于分辨矩阵的属性约简算法。

Monte Carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory. When comes to Bayesian classification, it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability. Then, it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one. At last, it can obtain the posterior probability distibution of each unlabelled classes by analysing these stochastic data.

蒙特卡罗是一种采用统计抽样理论近似求解数学或物理问题的方法，它在用于解决贝叶斯分类时，首先根据已知的先验概率获得各个类标号未知类的条件概率分布，然后利用某种抽样器，分别得到满足这些条件分布的随机数据，最后统计这些随机数据，就可以得到各个类标号未知类的后验概率分布。

What are your goals and strategies for growth?

你的成长目标和策略是什么？

And unto the angel of the church in Sardis write; These things saith he that hath the seven irits of God, and the seven star I know thy works, that thou hast a name that thou livest, and art dead.

3：1 你要写信给撒狄教会的使者，说，那有神的七灵和七星的，说，我知道你的行为，按名你是活的，其实是死的。