矩阵的三角分解(LU分解)是矩阵分解中最简单、最基础的一种。
Matrix's triangular decomposition (LU decomposition) is the simplest and most basic kind of decomposition in matrix decomposition.
通过矩阵的初等变换可实现矩阵的满秩分解和强满秩矩阵的三角分解。
Full rank decomposition of matrix and triangular decomposition of strongly full rank can well be realized by elementary transformation method of matrix.
直接法中的平方根法，就是利用对称正定矩阵的三角分解而得到的求解对称正定方程组的一种有效方法。
Square root method is one of direct methods, which is an effective method for the solution of symmetrical positive liner equations through triangle decomposition of symmetrical positive matrix.
LU分解是一种将非奇异矩阵进行三角分解的方法，而数字图像也可以看作矩阵。
LU decomposition is a triangular decomposition approach of non-singular matrix, and the digital image can be seen as a matrix.
对于特殊矩阵的快速三角分解算法的研究，目前主要是对一些较简单的矩阵进行的。
It is mainly to some simple matrices to the research of the fast triangular factorization algorithms of special matrices up to now.
对应特征点的三维重建是根据三角测量的方法计算其投影矩阵，然后用奇异值分解求出特征点的三维齐次坐标。
Feature points' 3d coordinates are computed through singular value decomposition of projector matrix, then compute projector matrix by triangulation.
对应特征点的三维重建是根据三角测量的方法计算其投影矩阵，然后用奇异值分解求出特征点的三维齐次坐标。
Feature points' 3d coordinates are computed through singular value decomposition of projector matrix, then compute projector matrix by triangulation.
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