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Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

机译:基于神经网络的信号模式识别在铁轨自动测试中的应用

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The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basis of measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.
机译:本文介绍了神经网络在铁路超声测试车收集的测量数据中识别信号模式的应用。测量信号的数字转换可以存储和处理大量数据。已经提出了基于所测量的信号幅度来识别所获得的模式的智能,有效和自动过程的阐述。该测试仅显示两类模式识别。在作者看来,如果我们提供足够数量的培训数据,则提出的方法适用于识别许多课程的系统。

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