matlab-pid-1

其基本思想是：采用信号与噪声的状态空间模型，利用前一时刻地估计值和现时刻的观测值来更新对状态变量的估计，求出现时刻的估计值。它适合于实时处理和计算机运算。 (The basic idea is: use of signal and noise state-space model, the estimated value of the previous time and are always observations to update the estimated state variables, find an estimate of time there. It is suitable for real-time processing and computing.)

通信系统仿真与Matlab应用,第二版,完整Matlab源代码(Conduct anti信Services department suddenly Ling与using Matlab crown, old woman版Um, finished entire Matlab Daitou Tungsten measurements)

PlotPub是一个自由和开放源码MATLAB库创建美丽、出版质量图立即从MATLAB生成或保存MATLAB图文件的数字。此库提供了一个简单的和简单的方法来修改几乎所有方面的一个MATLAB的数字。它可以出口的数字EPS、PDF、JPEG、PNG、TIFF可调的决议。PlotPub中的默认设置可以产生体面，出版准备开箱图。(PlotPub is a free and open source MATLAB library for creating beautiful, publication quality graphs instantly generated MATLAB figures or saved MATLAB fig files. This library provides a simple and easy way to modify almost all aspects of a MATLAB figure. It can export figures in EPS, PDF, JPEG, PNG and TIFF with adjustable resolution. The default settings in PlotPub can produce decent, publication ready graphs right out of the box.)

Simulate MIMO system with BER and capacity

上海交通大学硕士论文基于小波技术的matlab车牌识别(License Plate Recognition)

model de turbine eolienne 180kw medel utile pour l utilistion derecte dans les generatrices eoliennes

Excel files and MATLAB programs for endogenous growth models

matlab GUI编程实例之归一化二阶系统演示界面设计。(matlab GUI programming examples of presentation interface design owned by one of the second-order system.)

模糊PID控制程序，制定了模糊规则，pid控制更加精，在经典PID控制基础上加上模糊控制，是控制速度更快 (Fuzzy PID control procedures, developed a fuzzy rule, pid control is more refined, based on the classic PID control plus fuzzy control, control faster)

模拟一群鸟捕食的情景，从而达到优化目标函数的目的，这就是粒子群算法！起初在可行的空间中随机的产生一群粒子，然后让每个粒子开始在虚拟的空间中向四面八方飞翔，并且每个粒子都记下他们飞过的适应值（也就是目标优化函数）最高的点，而且整个粒子群有一个最高适应值个体，这样，粒子在飞翔的时候尽量朝向自己曾飞过的最好的点和集体的最好的点。最后达到收敛到近似最优点的目的。 (Simulation of a group of birds preying on the scene, so as to achieve the purpose of optimizing the objective function, that is, PSO! At first, where feasible, have a space in a group of random particles, and then let the beginning of each particle in a virtual space to fly in all directions, and each particle they have in mind over the fitness value (that is objective optimization function) the highest point , and the whole particle swarm adaptation has a maximum value of the individual, so that particles in the fly when he had flown as far as possible towards the best point and collective best point. Finally reaching the merits of convergence to approximate most purposes.)