DES

粒子群算法,自己编的一个程序，可以实现，运行main函数(Particle Swarm Optimization)

用matlab画出齿轮啮合面的三维模型，用于研究齿轮的啮合特性(Matlab to draw three dimensional models of gear meshing, used to study the gear meshing characteristics )

两个matlab编写的图像分割算法，分水岭和模糊C均值聚类算法(matlab codes, watershed algorithm and fuzzy C means clustering algorithm)

prop integ deri control systems

二进制ook调制 matlab实现仿真程序(ook modulation)

滤波函数，关于平滑滤波，巴特沃斯滤波等等滤波函数(lvbo function about something somthing the waves)

本程序用matlab工具编程,采用lms算法实现信道估计.其中信源是+-1二值随机码,信道为多径(3路径)信道.(the procedures used Matlab programming tools using LMS algorithm channel estimation. Which source is-1 two random codes, channel more Drive (Route 3) channel.)

说明：  功能一句话：Design Linear-Phase FIR using Window: rectangular window,Hamming window,Bartlett window。是学习信号处理FIR滤波器设计时很好的代码。(Design Linear-Phase FIR using Window: rectangular window,Hamming window,Bartlett window)

说明：  永磁同步电机id=0 FOC控制，SVPWM算法simulink仿真模型，波形良好(Permanent magnet synchronous motor id = 0 FOC control, SVPWM algorithm Simulink simulation model, good waveform)

说明：  SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能： 实验设计：中心复合设计，全因子设计，拉丁超立方体设计，D-optimal和maxmin设计。 代理：克里金法，多项式响应面，径向基神经网络和支持向量回归。 错误和交叉验证的分析：留一法和k折交叉验证，以及经典的错误分析（确定系数，标准误差;均方根误差等;）。 基于代理的优化：高效的全局优化（EGO）算法。 其他能力：通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities: Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs. Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression. Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others). Surrogate-based optimization: efficient global optimization (EGO) algorithm. Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.)