The sparse vector method enhances the efficiency of matrix solution algorithms by exploiting the vector sparsity. It has been successfully applied to many problems arising in power systems.
稀疏向量法通过利用向量的稀疏性来提高求解矩阵方程的效率，它被成功地应用到电力系统分析的众多问题。
Owing to its sparsity of structure, new matrix greatly simplifies the projection operation during images reconstruction, which greatly improving the speed of reconstruction.
该矩阵由于其构成的非常稀疏性大大简化了图像重建过程中的投影计算，从而提高重建速度。
According to signals sparsity by Curvelet transform, the mixed matrix can be estimated with C-means cluster analysis, and the estimated value is looked as initial value of BSS algorithm.
该方法利用Curvelet多尺度几何分析后信号的稀疏性特点，采用了C - means聚类方法寻求混合矩阵估计值，把该估计值作为算法初始值。
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