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Lasso算法源代码,stanford开发的,绝对可靠(Glmnet for Matlab- Lasso (L1) and elastic-net regularized generalized linear models)

3D流场计算，程序简单非常容易看懂。适合初学者学习(3D flow field)

此程序为香农编码的程序实现的过程及相关参数和结果。(shannon)

说明：  Matrix multiplication explained in detail for C++

计算天体力学中常用的HANSEN函数,对偏心率小于0.1时适用(This code for hansen function )

地球物理中的G-S变换，电磁场频率域变换到时间域。(Geophysics in the GS transformation, electromagnetic frequency domain transform to the time domain.)

最小二乘法数据处理软件，翻遍计算的程序，应用于各种优化算法(math caculateor)

利用c语言编写了迭代法解线性方程组的源程序，大大简化了计算量。(Use the C language source code of the iterative method for solving linear equations, which greatly simplify the calculation, suitable for solution of complex equations)

％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法， ％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵， ％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。 ％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解( Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution)

该程序用于形成节点阻抗矩阵，按程序要求格式输入线路数据linedata，Zbuild（linedata）形成节点阻抗矩阵(The procedures used for the formation of the node impedance matrix format input line data linedata procedural requirements of Zbuild (linedata) node impedance matrix)