By using the method of matrix singular values decomposition, the general expressions of the least squares solutions are given.
利用矩阵的奇异值分解和矩阵分块方法，得到了最小二乘解的一般表达式。
Digital image is transformed into singular value matrix that contains non-zero singular values by singular value decomposition (SVD), the image is compressed.
通过对图像进行奇异值分解，将一幅图像转换成只包含几个非零值的奇异值矩阵，实现图像压缩。
Any image can be considered as a matrix. Singular values (SV) of the matrix have some important properties adaptable to image recognition.
每一幅图像都可以认为是一个矩阵，而矩阵的奇异值具有很多适合图像识别的特征。
The relationship between the eigenvalue, eigenvector and the rank of the product of matrices AB and BA is discussed, and the factorization of the singular values of matrix a is obtained.
讨论了矩阵乘积ab与BA的特征值、特征向量及秩等的关系，并得到了矩阵的奇异值分解。
A computing method of coefficient matrix is given. For a few special points including singular points, the numerical values of solid Angle of a cylindrical bottom surface open to these special points.
对包含奇异点在内的几个特殊点给出了柱底面对这些点所张立体角的值，并给出了电测井积分方程系数矩阵的计算方法。
In this paper, some inequalities about singular values of normal matrices are established by the properties of compound matrix and the relation between eigenvalue and singular value of matrix.
本文讨论了一般正定复矩阵的两个性质，给出了正定复矩阵特征值的界，并给出了正定复矩阵行列式的模满足的一个不等式。
In this paper, some inequalities about singular values of normal matrices are established by the properties of compound matrix and the relation between eigenvalue and singular value of matrix.
本文讨论了一般正定复矩阵的两个性质，给出了正定复矩阵特征值的界，并给出了正定复矩阵行列式的模满足的一个不等式。
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