然后将其与地震子波褶积，使其求解结果与实际地震数据的最小平方问题归结为求解一大型稀疏矩阵方程，并采用奇异位分解法求解。
The least square problem of the convolution result and real seismic data can be considered as the solution of a huge rarefactional matrix equation, which can be solved by singular value decomposition.
本文主要是论述稀疏非负矩阵分解算法在矿产资源定量预测中的应用研究。
In this article, the sparse non-negative matrix factorization algorithm is applied to quantitative predict the mineral resources.
对于一般的带状矩阵，详述对对称与非对称三对角化矩阵做QR分解后，Q矩阵与R矩阵的稀疏元素分布型态。
For a general banded matrix, discuss the sparsity pattern of the Q and R matrices from the QR decomposition of symmetric and non-symmetric tridiagonal matrices.
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