推导得到两种迭代学习辨识算法：迭代学习贝叶斯法和迭代学习随机牛顿法。
Two prototype algorithms of iterative learning identification, iterative learning Bayes and stochastic Newton algorithms, are proposed with detail.
用基于贝叶斯法和经典法数据综合方法将分系统的试验数据转为系统试验数据。
The subsystem test data are transformed into the system test data using the data synthesizing method based on the Bayes method and the classical method.
首先阐明了极小子样高可靠性成败型产品试验评估的重大意义及通常用贝叶斯法解决该问题时所遇到的困难。
The importance of Bayes , estimation for extreme small sample, high reliability, safe or failure pattern is explained in this paper, the difficulty in solving these facts is involved.
贝叶斯模型平均法用来综合各模型的结果并提供一种反映模型选择和抽样变异性的不确定性度量。
Bayesian model averaging was used to combine the results across models and to provide a measure of uncertainty that reflects the choice of model and the sampling variability.
传统方法的适用范围计较狭窄，只能检测一种假说，但是贝叶斯过滤法可以同时检测一系列假说，并找出可能性最大的一个。
Classical methods are narrow, testing only a single hypothesis, but Bayesian methods can evaluate a whole set of scenarios and figure out which is the most likely.
与较早的研究不同的是，格列格雷运用了统计学的一种方法——贝叶斯过滤分析法。
Unlike earlier studies, Gregory used a branch of statistics called Bayesian analysis.
研究了人脸检测的贝叶斯特征判别法，该方法包括三个部分：原始图像的特征判别分析、人脸区和其它区的统计建模以及贝叶斯分类器。
The main idea of which consists of three parts: the discriminating feature analysis of the images, the statistical modeling of face and non-face classes, and the Bayes classifier for face detection.
研究方法：GM（1，1）模型、贝叶斯方法及先行指标法。
Methods of GM(1,1) gray prediction, Bayesian and antecedence index were employed.
本文主要探讨利用贝叶斯估计法改进特尔斐预测精确度的可能性。
This paper primarily deals with the possibility to improve the forecast precision for Delphi method by use of Bayes' estimation.
对隐含时间表达的识别，即汉语情态的分析，采用贝叶斯分类法进行动词分类和情态分类。
For implicit temporal expression recognition, witch is also called as Chinese situation analysis. The Bayes classification is used for Chinese verb classification.
提出了一种基于贝叶斯网络的故障树分析法并应用于配电系统的可靠性评估。
Afault tree method based on Bayesian network for Reliability Evaluation of Distribution System is presented.
进行了新方法、原贝叶斯高分辨方位估计方法与多重信号特征法（MUSIC）和极大似然估计法（MLE）的性能比较研究，揭示了新方法的优越性。
The new method and original Bayesian high-resolution DOA estimator are compared with other typical methods like MUSIC and MLE, and the superiority of the new method is revealed.
当用户行为偏离特征模型时，利用基于最小风险的贝叶斯判别法，可以实时有效的判断出用户的身份。
When the deviation from the model is found, the system can determine the identity of the user.
当用户行为偏离特征模型时，利用基于最小风险的贝叶斯判别法，可以实时有效的判断出用户的身份。
When the deviation from the model is found, the system can determine the identity of the user.
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