广义奇异值分解,generalized singular value decomposition
1)generalized singular value decomposition广义奇异值分解
1.Then,by thegeneralized 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 thegeneralized 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 thegeneralized 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。
英文短句/例句
1.Simulation of 3-D computerized ionospheric tomography based on generalized singular value decomposition algorithm基于广义奇异值分解算法的电离层三维层析模拟
2.Apply singular value decomposition and generalize inverse of the matrix to discuss the existence and uniqueness of the solution of the standard linear programming problem.用矩阵的奇异值分解和广义逆讨论标准线性规划问题解的存在性和唯一性问题.
3.singular value decomposition of image matrix影像矩阵的奇异值分解
4.Singular traveling wave solutions of a generalized Camassa-Holm equation广义Camassa-Holm方程的奇异行波解
5.PARALLEL IMPLEMENTATION OF SINGULAR VALUE DECOMPOSITION FOR TERM-DOCUMENT MATRIX IN LATENT SEMANTIC ANALYSIS潜在语义分析中词汇-文本矩阵奇异值分解的并行实现
6.A Feature Analysis of Numerical Solution forPartial Differential Equations;偏微分方程组数值解奇异性特征分析
7.Singular-value Decomposition in Time Series Analysis奇异值分解在时间序列分析中的应用
8.Image Watermarking Algorithm Based on Blocked SVD基于分块奇异值分解的图像水印算法
9.An Extension of Boundary Value Problem of Function Classes in Solutions with Singularities of High Order;具有高阶奇异解的函数组边值问题的推广
10.Positive Solutions of Singular Boundary Value Problem of Fourth ODE;四阶常微分方程奇异边值问题的正解
11.Face Expression Recognition Based on Singular Value Decomposition;基于奇异值分解的人脸表情识别研究
12.Kronecker product and singular value decomposition of weighted extended matrix;Kronecker积与加权延拓矩阵的奇异值分解
13.A New Method of Tremor Diagnosis Based on Singular Value Decomposition of EMD基于EMD奇异值分解诊断震颤的新方法
14.Digital Image Watermarking Algorithms Based on Singular Value Decomposition基于奇异值分解的数字图像水印算法
15.Noise Reduction of Frequency Response Function Using Singular Value Decomposition基于奇异值分解的频响函数降噪方法
16.Algorithm of Shot Boundary Detection Based on Singular Value Decomposition视频镜头边界检测中奇异值分解算法
17.A Method of Image Compression Based on Singular Value Decomposition一种基于奇异值分解的图像压缩方法
18.SINGULAR VALUE DECOMPOSITION AND ALGORITHM OF o-SYMMETRIC MATRIXo-对称矩阵的奇异值分解及其算法
相关短句/例句
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 thegeneralized 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 andgeneralized 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
3)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。
4)Generalized singular value广义奇异值
5)product-product singular value decomposition of matrix triplets三矩阵的乘积型广义奇异值分解
6)Singular value decomposition奇异值分解
1.Application of singular value decomposition (SVD) in solution of T_2 relaxation spectra from nuclear magnetic resonance (NMR) log data;应用奇异值分解算法的核磁共振测井解谱方法
2.Random noise attenuation using predictive filtering in F-X domain by singular value decomposition;F-X域奇异值分解预测滤波法随机噪声衰减
3.Application of matrix singular value decomposition (SVD);矩阵奇异值分解(SVD)的应用
延伸阅读
广义特征值问题数值解法见代数特征值问题数值解法。
