The fault diagnosis system is classed into data fusion level module, feature level module and decision fusion level module according data fusion method.
将故障诊断系统按数据融合的方法分为数据级融合模块、特征级融合模块和决策级融合模块。
The feature level module adopts RBF neural network to extract feature of data and to make feature fusion.
特征级融合模块采用RBF神经网络，其功能是提取数据特征进而特征信息融合。
According to the fusion levels, there are data level, feature level, decision level included in data fusion.
从融合的层次结构出发，数据融合技术可分为数据级、特征级和决策级三个融合层次。
Situation assessment is an important level in data fusion system.
态势估计是数据融合体系中的一个重要层次。
These data can be used to estimate the lifetime of plasma facing components and analyze the impurity level in core plasma of fusion reactors.
这些数据对估计对等离子体部件的寿命和堆芯等离子体中的杂质水平是有意义的。
These data might be useful to estimate the lifetime of plasma facing components and to analyze the impurity level in core plasma of fusion reactors.
这些结果对估计面对等离子体的部件寿命和分析聚变堆堆芯等离子体中的杂质水平估计是很有用的。
The fusion can be made on both the data level and the decision level.
该融合既可在数据层进行，也可在决策层进行。
The generalized model characterizing most remotely sensed data pixel-level fusion techniques is very important for theory analysis and application.
研究遥感数据像素级融合统一模型及相应的实现技术具有重要的理论和应用价值。
The data fusion level module mainly handles the metrical data of multi-sensors and extracts the feature of faults.
数据级融合模块主要对多传感器的测量信号进行处理，提取出故障诊断的特征信息。
The data of GIS is fused through out the modeling when the image understanding is running. The fusion is high-level one of GIS with RS.
模型中GIS属性数据惯穿遥感图像理解的全过程，是一种高层次的数据融合，且GIS数据特征的提取、处理和遥感图像理解是高度并行的。
Then, a multi-level and multi-hierarchical blackboard model is brought forward, which can be applied to situation assessment of data fusion.
然后提出了一种用于数据融合中态势评估部分的分级多层黑板模型；
Summary of Background Data. Fusion procedures have been associated with adjacent level morbidities and facet joint pathologies in a considerable number of patients.
在大量的患者中，融合术已经与临近节段退变和关节突关节病理改变相关联。
In order to resolve the problem, the method of multi-sensor data fusion on decision level is submitted.
为了解决干扰情况下地震动信号发射源的定性问题，提出了在决策层上的多传感器数据融合的识别方法。
From the abstract level of the data which is to be dealed with, the image fusion technique can be divided intoto pixel level, feature level and decision level.
从待处理数据的抽象层次上分，融合技术可分为像素级、特征级和决策级三种。
An interactive algorithm of two-level data fusion based on evidence theory is presented. Different information-source data received by the data fusion system are classified in detail.
在充分利用信息处理中心的人工情报和其它信息源数据的基础上，提出了基于证据理论的交互式二级融合算法。
The data fusion level module mainly handles the metrical data of the multi-sensors, the soft metrical data and the working condition data of the system.
数据级融模块主要处理多传感器测量数据，软测量数据和系统的干扰数据。
We study the algorithms of feature-level fusion based on the viewpoint of dependence and independence multi-variant data analysis, respectively.
首先从多元数据分析的角度，研究了基于相关性的多元数据分析和基于独立性的多元数据分析的特征融合方法。
We study the algorithms of feature-level fusion based on the viewpoint of dependence and independence multi-variant data analysis, respectively.
首先从多元数据分析的角度，研究了基于相关性的多元数据分析和基于独立性的多元数据分析的特征融合方法。
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