jifen

用多重网格方法求解泊松方程，偏微分方程求解(use multigrid method to solve poisson equation, pde solver)

说明：  牛顿法又称牛顿-拉弗森方法（Newton-Raphson method），是一种在实数域和复数域上近似求解方程的方法。本程序收敛速度快，迭代步数可取大一些(Newton method, also known as Newton-Raphson method, is an approximate method for solving equations in real and complex fields. The program has fast convergence speed so the number of iteration steps can be larger.)

高斯消元法、高斯列主元消元法解线性方程组。程序由本人独立完全独立完成。版权所有！(Gaussian elimination method out PCA Gaussian elimination method for solving linear equations. I am independent program consists entirely independently. All rights reserved!)

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：  PRP共轭梯度法优化计算，采用FORTRAN语言(PRP conjugate gradient method optimization, the use of FORTRAN language)

蒙特卡洛资料，对于编写概率计算问题有较多的帮助，希望能帮到需要的人。(Monte Carlo)

求实对称矩阵的特征值特征向量，内有读入数据文件。(Realistic symmetric matrix eigenvalue eigenvector, there are read into the data file.)

无网格算法中的光滑粒子水动力学sph算法源程序（溃坝）(Meshless algorithm smoothed particle hydrodynamics sph algorithm source (dam))

说明：  该程序用有限元方法来处理标量亥姆赫兹方程，其实例是脊形介质波导中的光波。(The functino of the code is to slove Helmholtz equation by using finite element method (FEM). The example is an optical waveguide.)

based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the minimum representation error. While the importance of sparsity is much emphasized in SRC and many related works, the use of collaborative representation (CR) in SRC is ignored by most literature.