kriging

实现高斯施戴尔迭代，可以直接输出迭代矩阵，并且，误差可以手动修改。(computate guass-sedal process )

fortran code for LINEAR_WAVE PROPAGATION by forward time forward spase method.

简单的滤波代码，包含高通滤波，低通滤波，带通滤波和带阻滤波。( U7B80 u5E5 u6E4 u6E4 u6E1 u6E1 u6E2 U5E26 u963B u6EE4 u6CE2 u3002)

格子玻尔兹曼模型DnQm系列模型中应用较为广泛的D2Q7模型源代码，用于模拟流体的流动。(The D2Q7 model source code of the the Lattice Boltzmann the model DnQm series model is widely used to simulate fluid flow.)

MDVRP_遗传算法 可以运行 希望对大家有帮助(a solution to MDVRP ,i hope it can help you)

计算等径双圆筒透镜的场分布，并画出等位线分布图(Calculation of Electron Physics )

介绍MAPLE使用方法的书籍。网上关于maple的指导书很少，这个是不错的了。对初学者来说可以迅速上手，我当时就是因为临时需要才学的，边学边用，很快就上手了。(An introductory book of MAPLE, published in 2007. Easy to understand and use. Suitable for beginners and amateurs.)

％ 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)

说明：  用于求解数值算法最优化算法中的SQP算法(Solve SQP algorithm Numerical algorithm optimization algorithm)

牛顿插值法进行多项式逼近，matlab编译成功，直接可用(Newton interpolation polynomial approximation method, matlab compiled successfully, directly available)