MtlabCFD

ANSYS车桥耦合瞬态分析代码,实现车辆移动荷载加载(ANSYS-vehicle bridge coupled)

vc++实现编译原理中的LL(1)文法的编译过程,非常好用.(vc realization of the principle of compiler LL (1) grammar compiler course, very handy.)

基于Python编写的差分进化原理的带边界条件约束算法(A band constraint algorithm based on differential evolution algorithm)

说明：  应用fluent进行两相流的仿真，内容充实具体，简易使用，是进行两相流仿真的一个很好的算例。pdf文件。(Using fluent to simulate two-phase flow, the content is rich and specific, easy to use, is a good example of two-phase flow simulation)

基于投影逼近的子空间跟踪（PAST）方法，用于自适应盲信号分离(Based on the projection approximation subspace tracking (PAST) method for adaptive blind signal separation)

有限元方法fortran编程，包括二维三维线性非线性静态分析、稳定流瞬时流分析、振动问题、特征值问题、并行计算等。包含了所有子程序。(Finite element method fortran programming, including 2D and 3D linear and nonlinear static analysis, steady flow transient flow analysis, vibration problems, eigenvalue problems, parallel computing. Contains all subroutines.)

％ 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：  自己编写的期望最大化（EM）算法的MATLAB实现，里面有较为运行方法和程序说明，对新手有很好的帮助( I have written the expectation-maximization (EM) algorithm in MATLAB, which has run more methods and procedures described, there is a good help for the novice)

说明：  该文件是用C语言实现快速傅里叶变换的源代码，需要的朋友快下载(The document is used C language to achieve fast Fourier transform of the source code, need friends fast download)

C-N解偏微分方程的程序。解的是定步长的抛物型偏微分方程： du/dx - a * d2u/dx2 = 0 在程序中可以更改 a 的值以实现不同系数的解。在循环中改变 a 的值以实现变系数. 该说明在压缩包是也有(CN solution of partial differential equations procedures. Solution is scheduled to step parabolic partial differential equation: du/dx- a* d2u/dx2 = 0 in the procedure can be changed in order to realize the value of a different coefficient of the solution. Change in the cycle in order to realize the value of a variable coefficient. The note in the compressed packet is also)