FSV

利用Lax-wendroff两步差分格式求解一维激波管问题Fortran语言(Use a two-step Lax-wendroff Difference Scheme for Solving the one-dimensional shock tube problem Fortran language)

对信号进傅里叶变换，得到振幅谱和相位谱，并可画出振幅谱和相位谱。(The signal into the Fourier transform, the amplitude spectrum and phase spectrum and amplitude spectrum and phase draw spectrum.)

这个windows下可视化晶体结构的软件,可用于构造晶体,界面,表面...对于做第一性原理初始模型的构建以及结果的可视化分析特别有用处.(Under the windows crystal structure visualization software can be used for the crystal structure, interface, surface ... do first principles for the construction of the initial model and the results of visual analysis is particularly useful.)

湍流模型re计算流体力学软件udf 可以用于修改UDF文件(turbulence model FLUENT)

CHEMKIN 2 源代码，使用Fortran语言编写，需要的可以下载(CHEMKIN 2 source code, written in Fortran, need can be downloaded)

粒子滤波PF，无迹粒子滤波UPF，卡尔曼滤波KF，扩展卡尔曼滤波EKF等例程与比较。建议下载，清晰明了(Particle filter PF, Untraced particle filter UPF, Kalman filter KF, extended Kalman filter EKF and other routines and comparisons.)

计算基尔霍夫近似下镜面与非镜面的反射系数，同时得到距离散射点2米的接收功率(Calculation Kirchhoff approximation of specular and non-specular reflection coefficient, while the reception power obtained from the scattering points of 2 meters)

支持向量机和BP神经网络都可以用来做非线性回归拟合，但它们的原理是不相同的，支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。大量仿真证实，支持向量机的泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。本源码可以用于线性回归、非线性回归、非线性函数拟合、数据建模、预测、分类等多种应用场合(Support vector machines and BP neural network can be used for non-linear regression fit, but they is not the same principle, support vector machine based on structural risk minimization theory, generally considered its generalization ability than the neural network of strong . Inherent defect- a large number of simulation confirmed that generalization ability of support vector machine is stronger than the BP network, but also to avoid neural network training results unstable. The source code can be used for linear regression, nonlinear regression, nonlinear function fitting a variety of applications, data modeling, forecasting, classification)

粒子群算法，也称粒子群优化算法或鸟群觅食算法（Particle Swarm Optimization），缩写为 PSO。它具有精度高，收敛快等优点，广泛用于系统辨识、函数优化等领域。文件pso.m是粒子群算法辨识程序，在此基础上，需要自行编写目标函数计算程序以实现不同系统的参数辨识。(Particle swarm optimization (PSO), also known as particle swarm optimization algorithm or bird swarm foraging algorithm (Particle Swarm Optimization), abbreviated as PSO. It has the advantages of high precision and fast convergence. It is widely used in system identification, function optimization and other fields. The document pso.m is a particle swarm algorithm identification program. On this basis, it is necessary to write an object function calculation program to realize the parameter identification of different systems.)

说明：  利用Abaqus子程序UAMP实现PID控制。(PID control is implemented using the Abaqus subroutine UAMP.)