filter_final

说明：  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。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

本程序是基于非等距节点的正交多项式的最小二乘法拟合算法，该算法已经在vc++6.0下调试通过，经多次验证，本算法的拟合误差较小。(This procedure is based on equidistant nodes of non-orthogonal polynomial least squares fit algorithm, which has been in vc++6.0 through debugging, after repeated verification, the algorithm of fitting error is small.)

一般线性规划问题具有线性方程组的变量数大于方程个数，这时会有不定的解。当决策变量个数n和约束条件个数m较大时，单纯形法是求解线性规划问题的通用方法。 从线性方程组找出一个个的单纯形，每一个单纯形可以求得一组解，然后再判断该解使目标函数值是增大还是变小了，决定下一步选择的单纯形。通过优化迭代，直到目标函数实现最大或最小值(In general linear programming problems, the number of variables with linear equations is greater than the number of equations. When the number of decision variables n and constraint number m are large, simplex method is the general method for solving linear programming problems. Find out one by one from the linear equations of the simplex, each a simplex can get a set of solution, and then concludes that the solution is the objective function value increases or smaller and decided to choose the next simplex. By optimizing iteration, until the target function achieves the maximum or minimum value.)

非线性迭代偏最小二乘的MATLAB代码,可用于光谱数据的建模(MATLAB code of NIPLS)

文件1.f90：生成翼型naca0012的椭圆网格，并计算流场，给出壁面压力分布 文件2.f90：maccormack方法解一维burger s方程 文件3.f90：解一维laval管流动，其进出口均为亚音速，喉道后部有激波(File 1.f90: generate the airfoil naca0012 elliptical rotary cell, and calculate the flow field, given the wall pressure distribution file 2.f90: maccormack method to solve the burger' s equation, one-dimensional file 3.f90: solution of one-dimensional laval tube flow, its progress exports are subsonic, the back of the throat have shock)

说明：  使用matlab进行 有限元计算，内含多种方式方法，欢迎交流讨论(Finite element calculation using matlab)

计算机常用数值算法与程序(C++版) (Commonly used numerical algorithm of computer and program )

FFT+FT连续细化傅立叶变换分析校正法 还请各位多多指教。 参考自丁康老师《离散频谱校正技术》 (FFT+ FT for Fourier transform analysis of detailed correction method is also called upon the exhibitions. Ding Kang reference from the teacher, " Discrete Spectrum Correction" )

说明：  用于非线性常微分方程的解的重要的一类隐式或显式迭代法，使用龙格库塔计算激光器的速率方程。(An important class of implicit or explicit iterative methods for solving nonlinear ordinary differential equations is to use Runge Kutta to calculate the rate equations of lasers.)

并联机构 正反解 六自由度并联机构空间运动结算 实例分析(DOF parallel mechanism inverse solution space motion parallel mechanism settled case analysis)