visicity-model

Echo cancellation using NLMS adaptive filter

这是求多柔体转子纽马克法的程序。以拉格朗日方程为基础，结合有限元发计算(is seeking more flexible rotor Newmark Act procedures. To Lagrange equation, the FEM calculation)

QR分解法是目前求一般矩阵全部特征值的最有效并广泛应用的方法，一般矩阵先经过正交相似变化成为Hessenberg矩阵，然后再应用QR方法求特征值和特征向量。它是将矩阵分解成一个正规正交矩阵Q与上三角形矩阵R，所以称为QR分解法,(QR decomposition )

there is an other java project in eclipse explaine how to code a simple calculator with a motor class

mpi 版本mstm 程序用于计算非球形粒子散射问题(MSTM, MPI version)

dft频率测量算法，主要针对电网频率的测量(the dft frequency measurement algorithm)

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.)

Matlab 算法寻找Bessel函数的零点。(find the zero point of Bessel functions)

数值计算各算法的程序,包括:牛顿迭代法,超松驰迭代法,微分法等.对于初学数值分析这门课程的人有很大的帮助.(Numerical calculation procedure of the algorithm, including: Newton iteration, ultra-relaxation iteration method, differential method and so on. Beginner numerical analysis for this course were very helpful.)

弹性力学平面问题有限元fortran源程序，包括平面梁，刚架，内含输入文件及exe文件 (Finite element elastic plane fortran source code, including flat beam, frame, containing the input file and the exe file)