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dempster相关的网络例句

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Double channel sequence image produced by infrared scene generator and real target sequence image of double channel imager--AGEMA THV900 are detected and fused, and the results are satisfactory. data fusion ; D S evidence theory ; target detection ; infrared image

对于弱小目标,复杂背景、大气传输和自身噪声的干扰,引起传感器量测的不确定性,通过 D- S证据理论对多传感器的证据进行数据融合,能够达到较好的目标检测效果。1 基本概率分配函数、置信函数和似然函数D- S证据理论起源于 Dempster早

This paper is concerned with Dempster-Shafer evidential reasoning theory in data fusion system.

在不确定性处理算法中,D-S证据推理方法具有较好的应用结果。

Dempster-Shafer evidential reasoning is one of the most useful fusing methods, and has been successfully used in many areas.

一些人认为D-S证据理论缺乏严格的理论基础,只有概率论才是解决不确定性问题的唯一方法。

Because of the Dempster-Shafer Evidential Reasoning's broad usage and validity, it is surveyed in particular.

由于D-S证据理论在应用领域中的广泛性和有效性,我们对它们进行了着重研究。

The approach identifies all possible focal elements from the incomplete decision matrix, then constructs the DS-AHPs hierarchical structure model, calculates the basic probability assignment of each focal element and the belief interval of each decision alternative.

该方法首先对决策矩阵中属性值进行识别,生成DS-AHP方法的焦元集合;然后构造DS-AHP的判断矩阵,并运用Dempster合成法则对判断值进行合成,从而确定方案排序。

Based on the entropy theory and Dempster - Sharer evidential theory, the problems of information fusion in mechanical characteristic parameter and mechanical failure diagnosis ware studied.

利用信息论熵的相关理论和D-S证据理论,分别研究机械特征参数提取和机械故障诊断的信息融合问题。

At first,this paper introduces differences between Dempster-Shafer's evidence theory and Bayes' subjective probability theory and main definitions and algorithms on D-S evidence theory.

本文首先介绍了证据理论与贝叶斯主观概率理论对于解决不确定性问题的差异,证据理论的主要定义和算法。

In feature-level case, fully polarization information from SAR is used to combine with spectral characteristic from SPOT images, mainly to enhance land cover classification as well. Speckle noise was removed by Lee filter, followed by the maximum likelihood classifier based on different distribution was used for SAR and SPOT images (Based on Wishart distribution and multivariate Gaussian distribution respectively), to extract the conditional probability of each pixel for each class.

首先使用李式滤波器滤除全偏极雷达资料杂讯,接下来同样是使用採用最大似然法来分类融合影像,(不同的在於全偏极雷达影像使用Wishart机率分布,在光学影像採用multivariateGaussian机率分布)將每个类别中每个像元属於某个类别的机率值计算出来,再利用Dempster-Shafer evidence theory来结合这些类别的机率值。

We first denoise the SAR image by Lee filter.Next,the maximum likelihood classifier based on different distribution was used for SAR and SPOT images(Based on Wishart distribution and multivariate Gaussian distribution respectively),to extract the conditional probability of each pixel for each class.

首先使用李式滤波器滤除全偏极雷达数据噪声,接下来同样是使用采用最大似然法来分类融合影像,(不同的在于全偏极雷达影像使用Wishart几率分布,在光学影像采用multivariate Gaussian几率分布)将每个类别中每个像元属于某个类别的几率值计算出来,再利用Dempster-Shafer evidence theory来结合这些类别的机率值。

The experiment illustrates that the method of the multi-sensor fusion based on Dempster-Shafer theory needs less prior information and it is resultful and robust.

仿真表明,这种基於证据理论的多传感器加权融合方法只需要很少的先验信息,但具有较好的融合效果和鲁棒性。

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