coding

在有限元分析中的网格划分好坏直接关系到模型计算的准确性，这里是关于网格划分的一些讨论。(In in the analysis of finite element mesh is directly related to the accuracy of the calculation model, there is some discussion about grid division.)

fast fourier transformation

无约束优化问题的阻尼牛顿法python代码(Damped Newton Python code for unconstrained optimization problems)

SPH方法计算二维溃坝问题的源程序，个人觉得还可以(Two-dimensional dam break problem SPH method the source, individuals felt that I could)

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)

一个用于复杂网络研究中计算网络静态参数（度分布，簇系数等）的c程序（其中的数据是具体的可换成其他的数据）。很简单但是对于做复杂网络研究的却很有启发的哦。(a complex network for research computing network static parameters (distribution, Clustering coefficient, etc.) c (which is specific data can be replaced by other data). Very simple but so complex network of research is very enlightening oh.)

计算按频率抽取的基4快速傅里叶变换算法，与基2FFT相比，基4FFT的乘法量约减少25 。(Calculating frequency taken by fast Fourier transform algorithm base 4, compared with the base 2FFT the base 4FFT multiplication about 25 less.)

fortran语言的球谐函数离散坐标法大气传输模型主程序，可用于大气场景生成(FORTRAN， spheric harmonic function of the discrete coordinate method main program, the atmospheric transmission model can be used for the atmospheric scene is generated)

说明：  局部线性回归方法及其稳健形式已经被看作一种有效的非参数光滑方法.与流行的核回归方法相比,它有诸多优点,诸如:较高的渐近效率和较强的适应设计能力.另外,局部线性回归能适应几乎所有的回归设计情形却不需要任何边界修正。(Local linear regression methods and their solid form has been seen as an effective non-parametric smoothing method. Contrary to popular kernel regression methods, it has many advantages, such as: higher efficiency and stronger asymptotic adaptation design capacity. In addition, the local linear regression to adjust to the return of the design of almost all cases does not require any boundary amendment.)

这是用C++编写的 用高斯方法求解方程的方法 我想对与计算机数学的同学来说 可能会有用(It is written with C++ method for solving equations using Gaussian approach I want to mathematics and computer may be useful for the students)