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针对三维问题，建立四面体单元的有限元方法(Finite element method for establishing tetrahedron element)

基于Python编写的用于曲线拟合，最小二乘法(Based on Python for curve fitting, least squares method.)

说明：  此是多峰函数MATLAB程序，多峰函数在解决多峰曲线问题中经常会用到，有此程序代码可以省去很多麻烦。(This is a multi-peak function MATLAB program, multi-peak function, multi-peak curve in the settlement of the question is often used, there is such a code can save a lot of trouble.)

Douglas-Peucker algorithm for a 2-dimensional data with example in matlab.

安德森/计算流体力学/fortran源代码(第九章esimple算法）(Anderson/Computational Fluid Dynamics/fortran source code (Chapter esimple algorithm))

用MATLAB编写的遗传算法路径规划，可以提取一幅图中想要的目标，matlab开发工具箱中的支持向量机。( Genetic algorithms using MATLAB path planning, Target can be extracted in a picture you want, matlab development toolbox support vector machine.)

用蒙特卡洛模拟的方法计算美式期权的价格以及基本描述,能量熵的计算，sar图像去噪的几种新的方法。( Monte Carlo simulation method of calculating the American option price and basic description, Energy entropy calculation, Several new methods sar image denoising.)

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)

说明：  1.5MW风力机叶片功率系数Cp计算程序示例，采用梯形法数值积分计算(1.5MW wind turbine blade power coefficient the Cp calculation program examples, numerical integration using the trapezoidal method)

一个利用共轭梯度法的正则化实例： 通过输入矩阵的维数，利用共轭梯度法的原理，进行正则化计算；Morozov偏差原理(A conjugate gradient method using the regularization Example: Enter the dimensions of the matrix, using the principle of conjugate gradient method for regularization calculation)