According to the vector modal theory for any shape profile metallic grating, the diffraction fields are studied numerically.
本文根据任意槽形金属光栅的矢量模式理论，对正弦槽光栅和半椭圆槽光栅的情况进行了推导和数值计算。
A method using combined parameters of natural frequencies and modal components as input vectors for support vector machine is presented in this paper.
提出一种由固有频率和模态分量构成的组合参数作为支持向量机输入向量的方法。
Therefore, through structural modal analysis with different damage degree using ANSYS, get natural frequencies and mode shape data as neural network input vector after unitary.
因此，通过有限元软件ANSYS对具有各种损伤程度的结构进行模态分析，得到固有频率和模态分量的数据，经过归一化处理后作为神经网络的输入向量。
This fiber's polarization modes, transmitting constants and modal birefringence were computed by the full vector finite element method.
应用全矢量电磁场有限元方法，计算了保偏光纤的两个偏振模场的分布、传输常数及模式双折射。
For Inter-MB, a temporally statistical modal with regard to vector angle was established and the moving object was detected by using the neyman-pearson criteria.
然后建立时域上关于搜索块与参考块之间运动矢量夹角的概率模型，对于帧间预测宏块通过聂曼一皮尔迅准则进行运动判决。
The modal vector reduction, error localization and model updating methods are approached.
进而研究了模态向量减缩、误差定位和模型修改等问题。
The quadrature and Vector methods are very simple and efficient in experimental modal analysis. The difficulties will be met in the consideration of structures with close-modes.
在试验模态分析中分量法及矢量法是非常简便实用的，但在处理密模态结构时会出现问题。
The modal characteristics of dual core photonic crystal fibers(PCFs) are analyzed by a full vector supercell lattice overlapping model.
应用全矢量超格子叠加模型分析了双芯光子晶体光纤（PCF）的模式特征。
The state vector methd of cross-section and modal analysis methd are used to identify the support and modal parameters of the spindle unit of the single spindle longitudinal automatic lathe mod.
本文采用截面状态矢量法和模态参数识别方法识别出CM 1107单轴纵切自动车床主轴部件的支承参数和模态参数。
In candidate sentences selection module, the methods we used to compute the similarity between sentences and query are N-gram modal and Vector Space modal.
相关语句抽取部分的相似度计算使用了N元模型和向量空间模型。
In candidate sentences selection module, the methods we used to compute the similarity between sentences and query are N-gram modal and Vector Space modal.
相关语句抽取部分的相似度计算使用了N元模型和向量空间模型。
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