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。
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。
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。
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。
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