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posterior probability相关的网络例句

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

Using the Bayes's theory about a estimate,the article researches the problem of probability change points,then gives a concrete priori distribution and posterior distribution,as well as gives a judge to the existence of probability change points.

利用Bayes估计理论,研究概率变点问题,给出变点的一个具体先验分布和后验分布,并对变点的存在性作出判断。

In Bayesian statistics, it can be seen as the posterior distribution of parameter p of a binomial distribution after observing α-1 independent events with probability p and β-1 with probability 1-p.

在贝叶斯统计,它可以被看作是后分布参数P一二项分布后,观测α-1独立事件的概率P和β- 1与概率1 - P的。

First,much basic knowledge is introduced.Then,it importantly introduces my perspective : in this paper the estimations of the parameters and coefficient of contamination for the simple regression model and studied when its response variables are contaminated by another random variable sequence it discusses that the interval estimation of posterior confidence probability of parameters on coefficient of contamination by using the method of Bayes inference.

首先介绍了一些基础知识,然后重点介绍了我所做的工作:讨论简单回归模型中响应变量受到另一随机变量序列污染时,模型参数和污染系数的估计方法。

Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaus- sian sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival prob- ability, and detection probability are all Gaussian sums.

分析的结果表明,当初始的先验强度满足高斯或者可以表示成高斯和的形式时,通过将状态噪声、观测噪声、目标的繁衍、新目标的产生、目标的存活概率和检测概率表示成高斯和的形式,之后每个时刻的后验强度均能表示成高斯和形式。

It has been found that the MCMC approaches can estimate and derive the posterior joint probability distribution of the model parameters properly.

采用基于实测流量资料估计的置信区间可靠性作为评判标准,实验结果表明:就SMAR模型而言,MCMC方法能够更好地推求模型参数的后验分布。

The posterior probabilities give the probability of a particular state of nature, given a particular finding from the seismic survey.

后验概率给出了在特定的勘探结果下出现特定的自然状态的概率

Topics covered include subjective notion of probability, Bayes' Theorem, prior and posterior distributions, and data analysis techniques for statistical models.

包括:概率的主观定义,贝叶斯理论,先验和后验分布,统计模型的数据分析技术。

A character-codes model based pattern recognition method by using amplitude data of targets frequency response is proposed after the establishment of high frequency response equation of radar targets. The method uses the same unvariant character-codes to express the same target of different angles and uses sequential separating of regions of target's reference variables to obtain multiple coding vectors of all regions for every target. The category and pose of target can be determined after a two-staged classification processing such as coding processing of target range profile data and errors correcting processing of coded data. The two-stage classification results are used to target identification as posterior hypothesis to be tested by sufficient convincing and necessary convincing. The character-codes model based pattern recognition method is also adaptive to variation of target angles and controllable in error probability. Time-consuming and complicated iterative computation is not necessary in the train process of pattern recognition.

首先建立了雷达目标的高频频率响应方程,这种方程将目标多散射中心理论与目标局部谐振理论有机地结合起来;进而提出了目标多频响应结构成像方法,这种方法将瑞利区频率响应或谐振区频率响应曲线的不同部位用各种不同的近似方法去逼近,通过特征谱估计方法将目标的局部频响特征与宽带距离响应特征结合起来;然后提出了一种基于姿态角变化区域的序贯划分与多模匹配的特征编码识别方法,这种方法具有能适应目标姿态角的变化以及能控制识别的差错概率α等优点,在目标识别时只需要目标在少数有限个频率激励下的幅频响应数据。

This article took the materials importance;urgency and scarcity as the classified criterion, put the velues after being fuzzed as the input of PPSVM, selected the classification which is corresponding with the Max Posterior Probability as the output , the results of the classification are obtained finally .

把物资的重要性、时效性和缺口程度三个因素作为物资需求分级的评价标准,将模糊化后的评价值作为PPSVM的输入,选择后验概率最大所的类别作为测试样本的类别输出来完成整个分类过程,从而得到对应的分级结果。

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