在数据层融合中，使用模糊逻辑的统计方法识别系统类别、区分网络设备；
The information fusion technology was applied to collect the network information using several detecting tools. The information from different detecting tools was fused in different layers.
首先应用小波包变换对结构振动测试数据进行特征提取，通过不同传感器特征向量的合成完成数据层融合；
Firstly, Wavelet packet transform is introduced to extract features of vibration measured data and information fusion of data layer is conducted by assembling feature vectors of different sensors.
多分类器组合是对决策层的数据进行融合。
The multiple classifiers combination fuses the decision level data.
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。
In order to resolve the problem, the method of multi-sensor data fusion on decision level is submitted.
信息层采用分布式数据融合技术，融合处理网络中各单元节点获得的目标信息。
The distributed data fusion technology was adopted for information layer to deal with the target information gained by each unit node in network.
该融合既可在数据层进行，也可在决策层进行。
The fusion can be made on both the data level and the decision level.
其融合系统分数据层、特征层和决策层融合。
Its fusion system includes data layer, feature layer, and strategy layer fusion.
论述神经网络技术在图像数据层、特征层、决策层融合技术及融合前处理中应用的若干新进展；
Meanwhile the development of neural networks in the image fusion at pixel, feature and decision levels and other pre-fusion applications are dissertated.
提出包含应用层、接口层、集成层、适配层、数据层五层结构数据融合系统。
This paper presented a data integration architecture consisted of application-layer, interface layer, data integration layer, adapter layer and data layer.
这是通过深入观察两个流行的数据库抽象层，PEARDB和Metabase， 之后并且对它们进行了融合后获得的。
This was achieved by closely examining two popular database abstraction layers, PEAR DB and Metabase, and merging them.
这是通过深入观察两个流行的数据库抽象层，PEARDB和Metabase， 之后并且对它们进行了融合后获得的。
This was achieved by closely examining two popular database abstraction layers, PEAR DB and Metabase, and merging them.
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