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概率框架下
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  probabilistic framework
     Based on statistical characters of lightning currents, LEMP under a general probabilistic framework were discussed, the probability distribution and density functions of peak amplitude of LEMF were deduced. The probability distributions, cumulative probability distributions, means and standard deviations of peak electric field intensity and peak magnetic field intensity at different positions were calculated using multiple-integral method, and the results agree well with the ones obtained by Monte Carlo simulation.
     基于雷电流的统计特性,在具有一般性的概率框架下讨论雷电电磁场,导出电磁场峰值的概率分布函数及密度函数,采用多重积分法计算出不同位置处电场强度和磁场强度峰值的概率分布图和累积概率分布图,计算结果与蒙特卡洛模拟结果吻合。
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  “概率框架下”译为未确定词的双语例句
     We firstly discuss the separability of the blind sources based on sparserepresentation under the probability frame, and set up a group of probability inequalityand probability estimation which is indicate the connection of separability and numberof observation, the number of sources, the sparse degree of sources.
     我们在概率框架下讨论了基于稀疏表示的信号盲分离的可解性(可分离性)问题,并建立了一组关于可解性的概率不等式及概率估计.
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     Then it is proved that |AC||CC|holds except some particular cases and the conditions when AC = CC holds have been pointed out. Furthermore,It has been analyzed what influences the difference between AC and CC and concluded that both the prediction accuracy and the difference between FP and FN result in the difference between AC and CC.
     首先在统一的概率框架下给出了CC和AC的统计描述,阐明了二者在概率意义上的差异,并系统的给出了|AC||CC|的证明以及等号成立的充要条件,最后用计算机模拟的方法分析了AC与CC之间大小差别的影响因素,得出预测准确性的高低和|FP-FN|的大小是两个影响|AC-CC|大小的主要原因.
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  相似匹配句对
     PROBABILISTIC EVALUATION FOR STEEL FRAME COLUMNS OF TALL BUILDINGS
     高层钢框架柱的概率评估
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     Research of Probabilistic Framework for Multi-Agent System Model
     多Agent系统模型概率框架的研究
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     Probabilistic Logic Programming
     概率逻辑程序
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     Then,article also explains Struts' theory and every component.
     —Struts框架
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     Probability Experiments
     概率实验
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  probabilistic framework
The coupling of lightning electromagnetic field to electronic receiver under a general probabilistic framework is discussed.
      
We further analyse the relaxation function in a probabilistic framework, which allows to discuss different possible scalings according to the choice of specific hypothesis.
      
We invoke a simple probabilistic framework in which kernel density estimates are used to model distributions of brain activation foci conditioned on words in a given abstract.
      
This paper presents an approach to quantifying some of these uncertainties within a probabilistic framework.
      
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Visual tracking of human body movement is a key technology in a number of areas, such as visual surveillance and monitoring. In this paper we present a 2-D model-based method of human body tracking from a monocular video sequence. Morris & Rehg put forward a 2-D scaled prismatic model(SPM) for figure registration which has far fewer singularity problems than 3-D models. Here we extend it in a 2-D cardboard human body model with additional one DOF of width change. Based on this modified 2-D model rather than...

Visual tracking of human body movement is a key technology in a number of areas, such as visual surveillance and monitoring. In this paper we present a 2-D model-based method of human body tracking from a monocular video sequence. Morris & Rehg put forward a 2-D scaled prismatic model(SPM) for figure registration which has far fewer singularity problems than 3-D models. Here we extend it in a 2-D cardboard human body model with additional one DOF of width change. Based on this modified 2-D model rather than 3-D model in Bregler & Malik′s work, we also set up a mixture motion model for body movements and then solve motion parameters of the articulated body using EM in a statistical framework, where the model-based kinematic constraints are incorporated in a linear form. Tracking results from real video sequences are encouraging.

提出一种跟踪单眼图像序列中的行人 ,并恢复其运动参数的新方法 .在跟踪中采用了基于SPM (ScaledPrismatModel)扩展的二维纸板人模型取代三维人体模型 ,以获取更快的计算速度 .作者使用EM算法在概率框架下进行运动估计 ,同时 ,算法也考虑了混合的运动模型和运动约束 ,以减小解的搜索空间 .试验结果证明了该方法的有效性

Analysis and decision making are the critical steps in stock investment. Most of the existing methods suffer from deterministic representation of the quantitative analysis results as well as neglecting the bias on profit and risk of individuals. This paper presents a new approach of decision making on stock investment based on probabilistic model which can be used in the creation of Stock Investment Decision Support System. The new approach demonstrates the probabilities of different prices in the future via...

Analysis and decision making are the critical steps in stock investment. Most of the existing methods suffer from deterministic representation of the quantitative analysis results as well as neglecting the bias on profit and risk of individuals. This paper presents a new approach of decision making on stock investment based on probabilistic model which can be used in the creation of Stock Investment Decision Support System. The new approach demonstrates the probabilities of different prices in the future via statistics of the price history and estimates the expectation of profit and risk in a certain decision. With the optimization of individual utility function, decision is made on buying and selling prices. Compared with the existing approaches, the new one represents uncertainty model instead of deterministic process and considers on individual bias on profit and risk, which overcomes the deficiency of existing methods. Simulation experiments are conducted including evaluation on probability distribution of stock price markup and decision making on buying and selling prices. The result shows the feasibility of our new approach.

证券投资分析与决策是证券投资过程中重要的步骤。以往的证券投资分析与决策支持的方法的分析结论大多无法定量地衡量证券价格的走势的不确定性 ,忽略了个人对风险和收益的偏好。本文提出了一种新的基于概率模型的证券投资定量决策方法 ,可用于证券投资决策支持系统的构建。该方法通过统计历史数据 ,在概率的框架下预测未来的证券价格变化的各种可能 ,对某一特定决策所产生的期望收益和风险进行评估 ,并通过优化个人的效用函数进行决策 ,解决了确定买入卖出点的问题。对比以往的证券投资分析和决策方法 ,新的方法用不确定的模型代替了确定性的表示 ,并且从个人对风险和收益的偏好角度进行了考虑 ,克服了已有方法的不足之处。本文进行了仿真实验 ,对证券涨幅概率分布和买入卖出点的决策进行了评价 ,实验结果显示了该方法的有效性。

It requires knowledge of stochastic features of lightning electromagnetic pulse (LEMP) to study effect evaluation of the potentially harmful coupling of LEMP to the electronic systems. Based on statistical characters of lightning currents, LEMP under a general probabilistic framework were discussed, the probability distribution and density functions of peak amplitude of LEMF were deduced. The probability distributions, cumulative probability distributions, means and standard deviations of peak electric field...

It requires knowledge of stochastic features of lightning electromagnetic pulse (LEMP) to study effect evaluation of the potentially harmful coupling of LEMP to the electronic systems. Based on statistical characters of lightning currents, LEMP under a general probabilistic framework were discussed, the probability distribution and density functions of peak amplitude of LEMF were deduced. The probability distributions, cumulative probability distributions, means and standard deviations of peak electric field intensity and peak magnetic field intensity at different positions were calculated using multiple-integral method, and the results agree well with the ones obtained by Monte Carlo simulation.

获得雷电电磁场的随机特性,是研究雷电电磁场对电子系统有害耦合效应评估的基础。基于雷电流的统计特性,在具有一般性的概率框架下讨论雷电电磁场,导出电磁场峰值的概率分布函数及密度函数,采用多重积分法计算出不同位置处电场强度和磁场强度峰值的概率分布图和累积概率分布图,计算结果与蒙特卡洛模拟结果吻合。

 
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