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对应的特征的英文

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"对应的特征"怎么读用"对应的特征"造句

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  • characteristic of correspondence

例句与用法

  • The characteristic equations of the two equations are identical .
    两方程对应的特征方程是恒等的。
  • Very often , however , it will be desirable to machine the workpiece so that it has temporary features which do not appear on the design , or which do not correspond exactly to design features
    但是在加工实践中,往往会出现设计中没有的临时特征或与设计特征不完全对应的特征
  • While flda only can get one optimal discriminating vector , by maximizing the fisher criterion , due to that the rank of the between - class scatter matrix is at most 1 for binary - class problem
    但类间离散度矩阵的秩最大只能为1 ,决定了flda只能取一个判别方向(最大特征值对应的特征向量) ,无法利用其它方向的判别信息。
  • The first algorithm is the restarted and deflated lanczos algorithm . at each beginning , we rich approximate eigenvectors corresponding to a few of smallest eigenvalues in magnitude to the krylov subspace
    第一种算法是重新开始的带特征向量的lanczos算法,每次重新开始时,我们把一些绝对值较小的特征值对应的特征向量加入到krylov子空间。
  • Its main idea is to search for the corresponding characteristic points between base image and following image , and also project the following image to base image by computing the transformation between images with lmv
    主要思想是通过找基准图像和后续图像对应的特征点,以最小二乘法计算出图像的变换关系,把后续图像映射到基准图像的坐标系中。
  • In this paper , we discuss some bicyclic mixed graphs which have few vertices on the bicycles , and find the eigenvectors corresponding to their smallest eigenvalues have similar structure properties to those of uncyclic mixed graphs
    对于非奇异双圈混合图,本文对双圈点数较少的若干图进行讨论,发现其最小特征值所对应的特征向量与单圈混合图的情形有类似的结构性质。
  • One - dimension noise subspace - based method always assumes that only the minimum eigenvalue of the signal covariance matrix is the noise eigenvalue , and the corresponding eigenvector is the true noise vector and constructs the one - dimension noise subspace
    基于一维噪声子空间方法始终认定只有信号协方差矩阵的最小特征值才是噪声特征值,其对应的特征向量才是真正的噪声向量,并构成一维噪声子空间。
  • With the construction of adjacency matrices that can effectively describe an arbitrary topological graph , the eigenvectors of the same eigenvalue of the two matrices are calculated respectively and the possible isomorphic correspondences are established on the basis of their maximum impertinent groups
    摘要在构建有效描述任意图邻接矩阵的基础上,分别计算2个矩阵的特征值所对应的特征向量,并依据它们的极大无关组寻找可能的同构对应关系。
  • Based on the relationship between the eigenvalue order and the number of variations of the corresponding eigenvector , some necessary and sufficient conditions for the solvability of the above problems have been derived , and the corresponding algorithms are developed at the same time
    根据jacobi矩阵的特征值的顺序与其对应的特征向量的变号数的关系,我们给出了jacobi矩阵存在及唯一存在的充分必要条件,同时相应地给出了构造jacobi矩阵的算法和数值实例。
  • Based on the theory of reyleigh minimum , the minimum of energy function of neural network was mapped to the eigenvector that was mapped to the minimal eigenvalue of the generalized eigenvalue problem , by which the precise solution of minimal eigenvalue was gained while the neural network moving to the minimum of energy function
    本文应用reyleigh极小值原理,将神经网络的能量函数的极小点对应于广义特征值问题的极小特征值所对应的特征向量,在神经网络向着能量函数极小点运动的同时得到了极小特征向量的精确解答。
  • 更多例句:  1  2
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