FFT

有限体积法求解流动和传热问题的经典源代码(Classic source code finite volume method for solving the problem of flow and heat transfer)

一个简单的LM算法程序，可以帮助你理解LM算法，还包括LM的解释(The neural network control method is used to control the unit step input of the controlled object)

二维泊松方程的定解问题：用5点菱形异步迭代格式求解泊松方程，h=5/4 ,误差s=1e-6 (Differential method for Poisson equation)

下面我们将给出一些基于Galerkin有限元法的微型泵模拟结果，模拟过程在商业软件COMSOL Multiphysics 3.2中实现。数值求解采用压力修正算法——SIMPLE，它首先假设一个压力场，然后通过求解不可压缩流动的Navier-Stokes方程得到速度场。这些速度不需要满足Possion型连续方程，所以对压力场的修正也带来速度场的修正，最终满足质量守恒。求解速度场的同时计算电势场方程。这会得到Lorentz力，然后将其反馈回N-S方程并作为体积力处理。连续耦合Lorentz力和速度场直到Newton迭代收敛。 (Below we will give some micro-pump simulation results based on the Galerkin finite element method, the simulation process in the commercial software COMSOL Multiphysics 3.2. The numerical solution of pressure correction algorithm- the SIMPLE, it begins by assuming a pressure field, and then by solving the incompressible Navier-Stokes equations, the velocity field. These velocities do not need to satisfy the continuity equation of Possion type pressure field correction to bring the amendment of the velocity field, and ultimately to meet the conservation of mass. Solving the velocity field at the same time to calculate the potential field equations. This will be the Lorentz force, and then fed back to the NS equations and processing as a volume force. Continuous coupling of the Lorentz force and the velocity field until the Newton iteration convergence.)

6自由度自由漂浮空间机械臂运动学建模，广义雅克比矩阵(6 degrees of freedom of the free-floating space manipulator kinematics modeling, generalized Jacobian matrix)

实现有限域中乘法，输入二个普通二级制数，输出在本原多项式的乘法结果(Achieve limited multiplication field, enter the number of two-tier system of two ordinary output in primitive polynomial multiplication results)

The following is an example of how Microsoft Solver Foundation can be used to solve a constraint satisfaction problem (CSP) like generating a typical Sudoku problem. Sudoku http://www.codeproject.com/Articles/419389/Sudoku-using-Microsoft-solver-foundation In this article I do not attempt to explain everything there is to know about constraint satisfaction problems, but I will go over the concepts in the hope that even if you have never heard of CSP you will still get the idea.

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)

s-波分裂参数计算，应用时间延迟方式,用于计算各向异性参数(shear-wave splitting time-delay calculation)

采用最小二乘方法的高斯曲线拟合算法， 用C 语言编写. 包含子程序.(Gaussian Curving Fitting with C language)