另外，通过局域波分析可把复杂的实测数据分解成有限个基本模式分量，从而简化信号分析过程，降低信号分析误差。
In addition, complicated tested data are decomposed into several intrinsic mode functions by this way, which low analyzing error, and predigest processing.
经验模式分解（EMD）通过筛分过程将原始信号分解成若干个基本模式分量（IMF），可看作无需预设带宽的自适应高通滤波方法。
Empirical mode decomposition(EMD) is a signal processing technique to decompose data set into several intrinsic mode functions(IMF) by a sifting process.
局域波分析方法的重大突破在于用基于信号局部特征的多个基本模式分量来描述信号，并赋予每个基本模式分量具有实际物理意义的瞬时频率。
The main innovations embodied in this method are the introduction of the intrinsic mode functions based on local properties of signals, which make the instantaneous frequency meaningful.
该文提出了一种新的非平稳信号的时变参数ARMA模型分析方法，用它分析数据需两个基本步骤：首先，用一种信号分解方法把信号分解成一些基本模式分量。
In this paper, a new method for time-varying ARM A model is introduced. It includes two procedures. First, using one method of signal decomposition, a signal is decomposed into some basic components;
720p是安装时能够使用的最低视频大小；如果没有分量或DVI输出，请使用文本模式。
720p is the minimum usable installation video size; if you don't have component or DVI output working, use text.
分量视频支持720p和1080i显示，但是可能不支持1080p(如果不知道这些是什么，请参阅理解消费者电子视频模式)。
Component video can reliably support 720p and 1080i displays, but may not work for 1080p (see Understanding consumer electronics video modes if you're not sure what this is).
在典型观测模式下建立了低云的表观光谱辐射模型，研究了对云背景辐射有贡献的各个辐射分量的计算方法。
An apparent radiation model for typical detection is presented in this article, and the calculations of radiation contribute to the cloud radiation is studied.
运用电磁场理论详细分析了环状波导管内电磁场各分量方程、模式特征及其强度分布。
Equations of components, field properties and intensity distribution of the electromagnetic field of the annular waveguide are analyzed in detail with the theory of the electromagnetic field.
在另一种技术中，将光源层的点扩展函数分解成多个分量，并对每个分量确定一个有效亮度模式。
In another technique, the light source layer's point spread function is decomposed into a plurality of components, and an effective luminance pattern is determined for each component.
考虑了模糊特征分量对识别模糊模式的重要程度，给出了一种新的模糊模式识别方法。
A new method of fuzzy pattern recognition is put forward by considering the importance of eigenvector in recognizing fuzzy pattern.
对比基本ica模型，超定ica的实验结果估计出了同时发生的结肠动力模式数量，并消除了噪声分量。
Comparing to the basic ICA model, the overdetermined ICA estimated the number of colonic motor patterns that happened simultaneously, and eliminated the noise components largely.
图像的几何性质，比如区域周长和连通分量，在图像分割和模式识别领域得到了广泛的应用。
Geometric properties, such as perimeter and connected component, have been widely used in image segmentation and pattern recognition.
在此基础上，通过统计和推导，改进差分量化的模式，得到其优化算法。
Based on the algorithm, improving the mode of difference disposal, optimizing algorithm through the statistics and deduction.
从该电子密度模式和电离层波传播特性出发确定多径分量，计算短波信道相干带宽。
The coherence bandwidth of shortwave channel is calculated by using the density profile and wave propagation features in ionosphere.
先对丙二烯振动模式进行分类及构造投影算符，再用投影算符构造简正坐标分量，从而组合出丙二烯分子的15个简正振动模式。
Then the paper used the projection operator to structure the normal coordinate component, thus combined 15 normal vibration patterns of propadiene molecule.
在对总不确定度的A类分量及B类分量评定的合理简化的基础上，确定了总不确定度的表示模式，并介绍了它们的应用。
Based on the rational simplification for type a and B evaluation of general uncertainty, this paper confirms the general certainty, and introduces their applications.
利用局域波法将微弱的故障信号分解为有限的并且具有不同基本模式的分量，每个分量是单一成分信号，实现了信噪分离。
Weak fault signal was divided into finite local wave components with different simple-intrinsic modes, so that signal was separated from noise.
同时对所采集的车辆声音信号应用模式识别中的主分量分析法实现了车辆的简单分类，为实现车型识别作了一些初步的探索。
At the same time, vehicle types are classified using PCA method of the pattern recognition based on vehicle noise, and some primarily study is done for vehicle recognition.
先将非平稳时间序列进行经验模式分解，再对各个分量分别建模，最后将各分量预测结果进行组合。
Empirical mode decomposition is used for pre-processing. Decompose time series, then make models separately and combine all the values.
先将非平稳时间序列进行经验模式分解，再对各个分量分别建模，最后将各分量预测结果进行组合。
Empirical mode decomposition is used for pre-processing. Decompose time series, then make models separately and combine all the values.
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