先验概率值大于0.8的标在了分支节点处。
Values of Bayesian posterior probability greater than 0.8 are shown at the nodes.
在最大似然法的程序实现中，采用了最小距离法提供先验概率。
Minimum Distance algorithm is adopted to supply prior probabilities of each type required in Maximum Likelihood algorithm.
贝叶斯方式是依据新的信息从先验概率得到后验概率的一种方式。
Bayesian is one kind of method of posteriori probability obtained from priori probability according to new information.
先验概率与后验概率有不可分割的联系，后验概率的计算要以先验概率为基础。
The posterior probability is computed from the prior and the likelihood function via Bayes' theorem.
此方法有效地解决了在先验概率未知的条件下，如何动态可变且快速地划分模糊域的问题。
The solution of quick a nd dynamic division of fuzzy fields is given out by this method, without the know ledge of priori probability.
该模型首先假设系统的所有状态都是可能发生的，并对系统中的各个元件设定一个先验概率。
First, the occurrence of all the system states is considered to have an equal possibility and for each component in the diagnosis system set a prior probability.
然后，结合图像帧间的差分信息以及灰度分布的先验概率等因素将图像从空间域映射至统计域。
Then, every frame is mapped from spatial domain to statistical domain incorporating the factors such as the difference image from the consecutive frames and the prior distribution of a pixel density.
引入像素强度的先验概率分布模型，运用模拟退火算法选择合适的邻域结构，获得强度的最优估计。
The prior information of pixel intense distribution is introduced. Then simulated annealing algorithm is applied to choose the proper neighborhood structure, and the optimal estimate can be obtained.
在识别过程中，首先假设各乐器的先验概率相同，根据高斯混合模型得出的后验概率确定待识别乐器所属的种类。
In the process of recognition, the prior probability is supposed to be the same, the posterior probability is calculated according to GMM, and then the instrument class is determined.
针对模式分类中高置信度的先验概率分布难以设定的问题，提出了一种新的应用贝叶斯分析进行模式分类的方法。
To overcome the hardship of enacting the pre-probability distribution with high certainty factor, this paper proposes one novel way of applying Bayes analysis to classify pattern.
它通过市场调查增加信息量，对先验概率进行修正，从而提高决策者对未来可能性的把握，达到降低决策风险的目的。
It collects information by market investigation, amends the prior probability, and consequently increases assurance of the investor on future success, so that the risk of decision-making is reduced.
在会计决策分析中所采用的先验概率通常由会计人员的主观判断来确定，使用贝叶斯方法能够对其进行修正，使之更加符合实际。
The prior probability in accounting decision is usually determined by the subjective judgment of the accountant. It can be modified by using the Bayes's method in order to be close to fact.
在目标识别级重点讨论了基于D - S证据理论的目标识别融合，通过性能分析可知该算法具有不需要先验概率和条件概率密度等优点。
In object identification level object identification fusion based on D-S proof theory was discussed, performance analyzing is found that the arithmetic did not need probability distribution.
在目标识别级重点讨论了基于D - S证据理论的目标识别融合，通过性能分析可知该算法具有不需要先验概率和条件概率密度等优点。
In object identification level object identification fusion based on D-S proof theory was discussed, performance analyzing is found that the arithmetic did not need probability distribution.
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