LBM-code

说明：  相场法基础书籍的配套计算代码，对于学习相场法的基础同学来说极其有用(The supporting calculation code of the phase field basic book is extremely useful for the students who are studying the basic method of the phase field method.)

北京航空航天大学数值分析大作业第二题，有难度，这可是历年北航研究生转载最多的代码了(Beijing University of Aeronautics and Astronautics numerical analysis of large operating the second question, there is difficulty, this is the most over the years Beihang University Graduate reproduced the code)

这是一个对时间序列进行短时傅立叶变换的源程序,测试过,好用的.(This is a program for STFT,which had tested.)

说明：  非线性方程 Aitken加速收敛方法 二分法 割线法 牛顿微分改正方法(Nonlinear equation Aitken accelerated convergence method Dichotomy method Secant method Newton's differential correction method)

control souce code with LQR

A tensor product (ranks 1 and 2) matlab app

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.)

设T 是一棵带权树，树的每一条边带一个正权。又设S 是T 的顶点集,T/S 是从树T 中 将S中顶点删去后得到的森林。如果T/S中所有树的从根到叶的路长都不超过d ，则称T/S 是一个d 森林。(this is a project )

EKF uKF的matlab工具箱，适合做非线性滤波的仿真计算。(EKF uKF the matlab toolbox for nonlinear filter to do the simulation.)

fsolve函数求非线性方程组数值解，已经验证其正确性。(fsolve function for the numerical solution of nonlinear equations)