1) Generalized Singularity
广义奇异性
3) generalized singular value decomposition
广义奇异值分解
1.
Then,by the generalized singular value decomposition,a general symmetric solution of the minimum residual problem is obtained.
首先,分别给出了与矩阵最小剩余问题及其最优近似问题等价的线性方程;其次,用广义奇异值分解得到了与最小剩余问题等价的线性方程的对称解,即最小剩余问题的对称解;最后,通过寻求与最优近似问题等价的线性方程的对称解,从而得到了矩阵的最优近似问题的最优近似解。
2.
The necessary and sufficient conditions for the solvability of such solutions are derived by using the generalized singular value decomposition.
利用广义奇异值分解,导出了矩阵方程(A*XA,B*XB)=(C,D)有Hermite部分是半正定的解、Hermite半正定的解的充分必要条件,同时给出了解的通式。
3.
By applying the singular value decomposition(SVD) and the generalized singular value decomposition(QSVD),the sufficient and necessary conditions and the normal solutions for the inverse problem of anti-centrosymmetric matrix with a sub-matrix constraint are given,and the optimal approximate solution is obtained.
利用矩阵奇异值分解以及矩阵对的广义奇异值分解,给出了子矩阵约束下反中心对称矩阵反问题有解的充要条件及其通解表达式,并得到了最佳逼近解。
4) generalized singular-value decomposition
广义奇异值分解
1.
Acquires the least squares solutions of the matrix equation AXB=E,CXD=F by constructing the normal equation of the matrix equation and applying the generalized singular-value decomposition of coefficient matrices.
借助于矩阵方程AXB=E,CXD=F的正规方程及系数矩阵的广义奇异值分解,得到了此矩阵方程的最小二乘解。
2.
The necessary and sufficient conditions for the consistency of the equations with an anti-symmetric condition on solutions are derived using the full-rank decomposition,generalized inverse and generalized singular-value decomposition.
分别用满秩分解、广义逆和广义奇异值分解导出了具有反对称解的充分必要条
5) generalized singular perturbation approximation
广义奇异摄动降阶
1.
At the beginning of this paper, to avoid the potential ill conditioned balanced transformation, Schur methods for generalized singular perturbation approximation (GSPA) method and singular perturbation approximation(SPA) method are obtained, and the robustness of the algorithm is good.
首先推导了广义奇异摄动降阶和奇异摄动降阶的 Schur方法 ,解决了均衡变换可能出现病态的问题 ,并且算法具有较好的鲁棒性。
6) GSVD
广义奇异值分解(GSVD)
1.
The first three problems for the matrix equation AXB =C,(1) When S is the set all central symmetry matrices, we have studied ProblemⅠand ProblemⅡby using the generalized singular value decomposition(GSVD) and the canonical correction decomposition(CCD).
前3个问题针对于矩阵方程AXB = C,(1)当S约束条件为中心对称矩阵集合,我们运用矩阵对的广义奇异值分解(GSVD)解决了问题Ⅰ,对于问题Ⅱ,我们运用矩阵对的标准相关分解(CCD)给出了解决办法。
补充资料：连续性与非连续性(见间断性与不间断性)
连续性与非连续性(见间断性与不间断性)
continuity and discontinuity
11an父ux泊g四f“山。麻以角g、.连续性与非连续性(c。nt，n琳t:nuity一)_见间断性与不间断性。and diseo红ti-
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条