BZreaction_diffusion

在matlab里利用逆矩阵算法对于一个给定的波前来算它的泽尼克系数(Zernike Polynomial Coefficients for a given Wavefront using Matrix Inversion in Matlab )

说明：  一个简单的CZT chirp-Z变换例程(a simple example of CZT)

给定样本点，采用高斯核密度估计，求出概率密度分布函数。(It is good to use this method to evaluate pdf)

FCTVOF的主程序,其中FCTVOF是求解关于VOF值的运输方程的一种经典算法，可求出各时刻的各网格的VOF值，从而利用界面重构技术实现界面的重构。(FCTVOF main program, including FCTVOF is for solving the transport equation of VOF value a classic algorithm, can calculate the VOF value of each moment of each grid, so as to make use of the interface to refactor the technical implementation interface. )

相场法材料计算的modelc-alloy 对应的基础代码，自取基础有用(The basic code corresponding to modelc-alloy for phase field method material calculation, useful for self-extraction)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method and Newton' s method between a method that takes only a first derivative information, but to overcome the slow convergence of the steepest descent method shortcomings, but also avoid the need to store Newton and computing the inverse Hesse matrix and disadvantages, conjugate gradient method is not only to solve large linear equations of the most useful methods, large-scale nonlinear optimization solution is the most efficient algorithms)

这是学习分数阶傅里叶变换，必须的算法这是学习分数阶傅里叶变换，必须的算法这是学习分数阶傅里叶变换，必须的算法(the of fragnaii or fft)

分别对beta估计值模拟分析、非中心对称分布、卡方拟合优度检验、筛选抽样随机数抽取、有限样本性质模拟这5个内容进行了编程说明(The five contents of beta estimation simulation analysis, non-centrosymmetric distribution, chi-square goodness-of-fit test, random number extraction of screening sampling and Simulation of finite sample properties are explained by programming.)

F-K域偏移法和相移法偏移程序（C语言）(FK domain migration method and the phase- shift method migration program (C language))

采用随机数产生2到10阶的随机矩阵，并实现了矩阵的相关运算，比如：加减，乘除，求逆，求行列式(Using random Numbers generated random matrix from 2 to 10 order , and achieving relative to the implementation of the matrix operations, such as: add and subtract, multiple and divided, inverse and determinant)