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Francis QR method is efficient way to calculate the complex eigenvalue of matrix. 双步QR法是求解一般矩阵特征值问题的有效方法,但在实际应用过程中存在一些不足。
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。
A NEW CONTAINED REGION FOR EIGENVALUE OF MATRIX 矩阵特征值新的包含域
On the Eigenvalue of Two Kinds of Matrix 关于两类矩阵的特征值
A CLASS DOMAIN of NEW EXISTENCE THEOREM FOR EIGENVALUE OF MATRIX 矩阵特征值的一类新的存在性区域
In this paper, using the property of trace of matrix and the method of generating function, we obtain all the eigenvalues of a matrix which appears iii stability analysis. 摘要利用矩阵的迹的性质和发生函数方法，给出了稳定性分析中一个矩阵的所有特征值。
Minimax Value of Generalized Eigenvalue of Matrixes 矩阵广义特征值的极值
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。
The article firstly work out the eigenvalues of the matrix,then we decide the jordan block number of each eigenvalues and the progression of each Jordan block,this produces another method to work out matrix Jordan canonical form of matrix. 文章通过先求矩阵的特征值;然后确定属于每一个特征值的若当块的个数和每一个若当块的级数来给出矩阵若当标准形的另一种求法.
The eigenvalues of matrices are an important conception in matrix theory,but computing the precise eigenvalues of a matrix is very difficult. 矩阵的特征值是矩阵理论的一个重要概念,然而,求一个矩阵(哪怕是阶数很低的矩阵)的特征值的精确值,却是非常困难的。
Advance on Study of Matrix Attachment Region. 核基质结合区的研究进展。
Approximate computation on the maximum eigenvalue of matrixs 矩阵最大特征值的近似求法
The Quality for Rand and Index of Matrix Power. 矩阵乘幂的秩及其指标的性质。
We introduced the concept of block directed edge cover diagonal quasi dominant matrix,obtained a new nonsingularity criteria for matrices and distribution theorem on eigenvalues of matrix. 引进了拟块有向边覆盖对角占优矩阵概念;给出了新的矩阵非奇异判定定理和特征值分布定理.
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。
Similarly, the order of matrix multiplication is important. 同样,矩阵相乘的顺序也是重要的。
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。
The following illustration shows two examples of matrix addition. 下图显示了两个矩阵相加的示例。
Getting optimized eigenvalue of det[sI-(A-BK)] = 0 is the target of pole placement by selecting state feedback matrix K. 极点配置就是选择状态反馈矩阵K，使系统的本征多项式det[sI-(A-BK)]=0的本征值处于最适宜的数值上，即获得最优的根配置。
The structural performances are evaluated from the condition number (CN) of equilibrium matrix, and CN and minimum eigenvalue of stiffness matrix. 根据平衡矩阵的条件数和刚度矩阵的条件数与最小特征值，评价基本单元的结构特征。