该文描述了基于贝叶斯推理的目标跟踪算法，可应用于非线性、非高斯系统中。
The paper introduces the target tracking algorithms based on Bayesian inference, which can be applied in the systems of nonlinearity and non-Gaussianity.
用贝叶斯推理问题为实验材料，探讨了主体关联性对贝叶斯推理概率估计的影响。
Bayesian tasks were used in the present study to explore the influence of subject relevancy on Bayesian reasoning.
引入了贝叶斯推理的统计方法对检测结果进行分析，优化了系统结构，提高了检测效率。
By using the statistical method of Bayesian deduction, system architecture and detection efficiency can be improved.
贝叶斯推理的多信道频谱感知方法也是多分辨率频谱感知的基础，具有重要的应用价值。
This idea sheds a light to the more general multi-resolution spectrum sensing problem, and is of practical significance.
贝叶斯推理的模型和广义线性模型，加速寿命故障模式，Cox回归模型和分段指数模型。
Bayesian modeling and inference for generalized linear models, accelerated life failure models, Cox regression models and piecewise exponential models.
为改善周期精确级功耗分析的准确度和速度问题，使用多维特征参数建立贝叶斯推理的动态功耗模型。
To improve the accuracy and speed in cycle-accurate power estimation, this paper USES multiple dimensional coefficients to build a Bayesian inference dynamic power model.
贝叶斯推理是认知心理学的一个传统论题，人们生活中的许多推断和决策也往往都与贝叶斯推理有关。
Bayesian reasoning is a traditional thesis in cognitive psychology, and a lot of judgment and decision making in our lives can use this method.
采用文献综述的方法，从问题内容、信息格式，信息呈现方式等方面对贝叶斯推理的影响因素进行了分析和探讨。
Based on literature review, the essay analyzed and explored the influencing factors of Bayesian reasoning from the perspectives of information content, information format and information presentation.
贝叶斯推理在对付电子邮件中的垃圾信息以及其他与垃圾信息不相关的领域(比如客户亲和力引擎，或商业推荐引擎)均有突出的表现。
Bayesian inference has also gained prominence in E-mail spam-fighting, and in non-spam-related areas such as customer affinity engines (or, commercial recommendation engines).
最常见的统计方式称为贝叶斯推理，更详细的内容，可以参阅IBMdeveloperWorks 的另一篇文章（参见参考资料）。
The most common statistical approach is called bayesian inference and is explained in detail in another IBM developerWorks article (see Resources).
贝叶斯网络是目前不确定知识和推理领域最有效的理论模型之一。
Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是数据采掘的一个非常有效的工具，它能够定性和定量地分析属性之间的依赖关系，进行概率推理。
Bayesian network as, a very useful tool in data mining, can provide qualitative and quantitative relationship between attributes and probability inference.
所提出计算模型为贝叶斯网的概率推理提供了一种新的局部计算方法。
The proposed computation models will supply new local computation methods for Bayesian network probabilistic inferences.
贝叶斯方法的特点是使用概率去表示所有形式的不确定性，学习或其他形式的推理都用概率规则来实现。
The characteristic of the Bayes method is to use probability to express the uncertainty of all forms, learning and the reasoning of other forms are all realized with the rule of probability.
介绍主观贝叶斯方法数学理论，描述其在不确定性推理中的应用，给出两种求解方法。
This paper introduces the mathematics foundation of Subjective Bayes Method, describes application of reasoning under uncertainties and provides two ways to solve the uncertain question.
同时利用贝叶斯网络实现概率推理，便于描述故障特征的变化及对变压器故障原因的快速分析。
At the same time, probability reasoning can be realized by BN, which can be used to describe changes of fault symptoms and analyze fault reasons of transformer.
针对舰船战场损伤评估的多元信息特点，建立了在观测操作条件下的舰船战场损伤评估的贝叶斯网络推理算法。
Object to the multi sensors character in warship battle damage assessment, a Bayesian net inference arithmetic is up forward considering observation operation.
因此采用贝叶斯网络推理和诊断具有一定的针对性。
So application of Bayesian Networks for reasoning and diagnosis has a definite pertinence.
以特征信息结构树为基础，对贝叶斯网络模型进行推理，来获得客户需求的兴趣集中点。
Through reasoning Bayesian network model based on the features information construction tree of client requirement, the client requirement concentration is acquired.
该文介绍了贝叶斯网络推理算法，分析了态势估计问题的本质特征和推理模式。
This paper introduces inference algorithm of Bayesian network and analyzes intrinsic characteristic and reasoning mode of situation assessment.
以贝叶斯网络及其推理机制为基础，主要研究了贝叶斯网络在辐射源威胁等级评估方面的应用。
After the theory and inference mechanism of Bayesian networks was introduced, this paper mainly studies the application of Bayesian networks in emitter's threat level assessment.
实验说明，基于贝叶斯网络推理的知识可以不断修正先验知识，获得对客户流失等问题的正确认识。
Experiments prove that the priority knowledge can be corrected continually by inference information of Bayesian network, and help to solve the problem of subscriber churn.
最后，以自动门为应用对象，采用规则诊断与贝叶斯诊断集成推理技术，开发了自动门智能故障诊断系统。
Finally, taking ADRT as the application object, using the integrated inference technology of rule diagnosis and Bayesian Network diagnosis methods, we develop the intelligent fault diagnosis system.
介绍了贝叶斯网络的概念，给出一个实例，分析了贝叶斯网络推理的方法和过程。
This thesis gives a introduction to the concept of Bayesian networks, and gives one example, the method and process is presented to Bayesian networks inference.
研究了基于贝叶斯网络的推理模型以及基于此模型的推理算法。
The inference model based on Bayesian Network is discussed and the algorithm based on the model is presented.
贝叶斯学习是一种基于已知的概率分布和观察到的数据进行推理，做出最优决策的概率手段。
Bayesian learning is a probability method that makes optimal decision based on known probability distribution and recently observed data.
第五章，研究了将贝叶斯方法应用于范例推理中两个非安徽大学硕！
In the fifth chapter, We studies the application of the method of BN in the Retrieval and Maintenance of CBR.
本文构建了一个基于粗糙集和规则推理的贝叶斯网模型，并将其运用于现实病历数据进行挖掘工作。
This paper builds a Bayesian inference network model based on the Rough Sets and Reason Rules and apply it to fulfill the medical data mining work.
本文构建了一个基于粗糙集和规则推理的贝叶斯网模型，并将其运用于现实病历数据进行挖掘工作。
This paper builds a Bayesian inference network model based on the Rough Sets and Reason Rules and apply it to fulfill the medical data mining work.
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