normalization method

A new normalization method towards instruction substitution that was a commonly used metamorphism approach was proposed.

针对等价指令替换常用变形技术提出了相应的归一化方法.

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The method use FID and count by area normalization method.

该方法采用氢火焰离子化检测器(FID),并用面积归一化法进行计算.

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Additionally , a good normalization method, that is an amplitude normalization within frames, is also presented.

文中同时还给出了适合于话者识别的参数归正方法: 帧内幅度归正.

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The quantitative calculation is carried out by external standard and area normalization method.

采用外标面积归一化法进行定量计算。

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Results The contents of logan in and morroniside 98 % by normalization method of HPLC.

结果所得马钱苷和莫诺苷用归一化法98%.

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The output degression curve method and normalization method are more suitable for short-run forecast.

水驱递减法、归一化法比较适合短期开发指标的预测。

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The relative content of the components were determined with area normalization method.

应用峰面积归一化法确定了各成分的相对含量.

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A normalization method used to describe the amplitude of precursory anomaly

描述前兆异常幅度的归一化方法

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Methods: The amount of the components from the essential components were determined by area normalization method.

方法用归一化法测定各组分的质量分数,并用GC-MS 法对其化学成分进行鉴定.

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Using external channel data-input method, the content of crystalline water and water insolubles are calculated together with chloride by normalization method.

采用外部通道输入法，使结晶水和水不溶物参与氯化物测定结果共同作归一化（100%）计算。

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On the basis of constructing the time series data with the same time interval by interpolation method, and treating the data with normalization method, a time series RBF neural network model about soft-base sedimentation is established. The sedimentation is predicted by training the network model.

采用插值方法构建时间间隔统一的时间序列数据并进行归一化处理，在此基础上建立了沉降变形时间序列的RBF神经网络模型，通过训练网络模型来预测沉降量。

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Detailed ANN learning method and algorithm are given as well as sample normalization method to improve learning efficiency.

还较详细地推导了ANN的学习方法，并给出了详细的算法以及对学习样本进行正规化的方法，以提高BP算法的学习效果。

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The relative contents in percentage were calculated with Area Normalization Method.

面积归一化法计算相对含量.

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The key procedure in single station data preprocess was time domain normalization. After comparing some existing normalization method, we made some improvement of running absolute mean normalization, from which we achieved better results.

数据预处理中的关键步骤是时域归一化，研究中对比了已有的几种时域归一化方法，并对滑动窗绝对值平均方法作了适当的改进，取得了较好效果。

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This method made use of hydrogen flame ionization detector ( FID ) and counted by area normalization method.

该方法采用氢火焰 离子化 检测器,并用面积归一化法进行计算.

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