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- semisimple eigenvalue 半单本征值
- A class of eigenvalue problems is studied. 摘要研究一类特征值问题及其应用。
- An iteration procedure can be used to determine the eigenvalue. 迭代方法可用来确定特征值。
- We can not say for certain which eigenvalue will be obtained. 我们不能说一定得到哪个本征值。
- On these grounds, the sensitivity of semisimple multiple eigenvalues of generalized eigenvalue problems is defined, and the sensitive elements of matrix pairs can be determined. 以所得结论为基础，定义了广义特征值问题半单重特征值的灵敏度，给出了确定矩阵对中敏感元素的方法。
- Kurtosis is an eigenvalue of normal distribution of the image. 峰度是一个能表征图像是否呈正态分布的特征值。
- Chemotaxis, traveiling wave, existence, stability, eigenvalue. 趋化性;行波;存在性;稳定性;本征值
- Eigenvalue discussion diffusivity impact on the learning curve. 讨论特征值扩散度对学习曲线的影响。
- Skewness is an eigenvalue of symmetric distribution of the image. 偏斜度是一个能表征图像是否对称分布的特征量。
- To this end we shall first consider the following eigenvalue problem. 为此目的,我们将首先考虑下列的本征值问题。
- The scalar is then called the eigenvalue associated with the eigenvector. 参见矩阵的特征值与特征向量的几何意义。
- In this paper, we consider inverse eigenvalue problem for matrix A_n=D_n+B_n. 本文考虑矩阵A_n=D_n+B_n特征值反问题。
- Wilkinson J H.Algebraic Eigenvalue Problem[M].Oxford;Oxford University Press. 卢开澄.;计算机算法导引-设计与分析[M]
- Some applications of this method in the eigenvalue problems are demon-strated. 举例说明了这方法在本征值问题中的应用。
- An inverse eigenvalue problem for damped gyroscopic systems is considered. 本文考虑一类阻尼陀螺系统特征值反问题。
- The text however develops basic Riemannian Geometry, Complex Manifolds, as well as a detailed theory of Semisimple Lie Groups and Symmetric Spaces. 然而课程还将简单介绍了基本的黎曼几何和复流形的知识，并会详细讨论半单李群和对称空间的理论。
- We researched the subspace eigenvalue decomposition and weighted subspace fitting techniques in the beamspace. 在波束空间内，研究了相干信源子空间分解技术和加权子空间拟合技术。
- The Solutions of eigenvalue and eigenfunction for three non-self-adjont situation are summrized. 对三种非自共轭情形下的本征值和本征函数的求解方法进行了归纳总结。
- A criterion theorem of having no finite coverings for a finitely generated module M over a semisimple ring R is given. 对半单环上有限生成左模给出一个无有限覆盖的判定定理。
- It is found that the synchronization time of N linear SDE is determined by the second maximum eigenvalue of interaction matrix. 首先得到了N维线性随机动力系统的同步时间由其相互作用矩阵的第二大特征值决定。
