pso1

说明：  清华大学出版社的《MATLAB控制系统应用与实例》模糊预测源码(Tsinghua University Press &quot MATLAB control system applications and examples of&quot fuzzy predictive source)

使用matlab实现对空时分组码的协同分集系统进行性能仿真(Using matlab to realize synergies STBC diversity system performance simulation)

说明：  对于初学者学习matlab很有帮助，尤其在图像处理方面更是很好的啊。(For beginners learn matlab &reg helpful, especially in the image processing is very good.)

基于变频器的空间电压矢量PWM控制matlab程序设计与实现(Matlab program design and implementation of the inverter space voltage vector PWM control)

说明：  处理蠓虫分类的另一种网络方法，方法仅供参考(Another network approach to classification midges)

MATLAB7.0/simulink实现的全套的自抗扰控制器资料，包括mdl文件和S-function。(Auto-Disturbance Rejection Controller implement by MATLAB7.0/simulink。)

雷达信号处理 阵列波束形成 最小均方误差 采样协方差矩阵求逆 Capon波束形成等等(Radar Signal Processing)

小波变换及编码在图像图形处理中有着重要的应用，本压缩包属于小波编码及其演示的matlab库函数，希望对大家的学习有帮助。(Wavelet transform and image coding has important applications in graphics processing, the wavelet encoding and compression packages are demo matlab library function, we hope to help learning.)

遗传算法的电机优化程序，个人专门编写的，对于初学者来说，可以借鉴(function youhua1() 遗传算法 n-- 种群规模 ger-- 迭代次数 pc--- 交叉概率 pm-- 变异概率 v-- 初始种群（规模为n） f-- 目标函数值 fit-- 适应度向量 vx-- 最优适应度值向量 vmfit-- 平均适应度值向量 clear all close all clc 清屏 tic 计时器开始计时 n=20 ger=100 pc=0.9 pm=0.1 初始化参数 生成初始种群 v=init_population(n,44) 得到初始种群，22串长，生成20*22的0-1矩阵 [N,L]=size(v) 得到初始规模行，列 disp(sprintf( Number of generations: d ,ger)) disp(sprintf( Population size: d ,N)) disp(sprintf( Crossover probability: .3f ,pc)) disp(sprintf( Mutation probability: .3f ,pm)) sprintf可以控制输出格式 待优化问题)

NW小世界网络的构成原则为：从一个环状的规则网络开始，网络含有N个结点，每个结点向与它最近邻的K个结点连出K条边，并满足N>>K>>In(N)>>1。随后进行随机化加边，以概率p在随机选取的一对节点之间加上一条边。其中，任意两个不同的节点之间至多只能有一条边，并且每一个节点都不能有边与自身相连。改变p值可以实现从最近邻耦合网络(p=0)向全局耦合网络(p=1)转变。在p足够小和N足够大时，NW小世界模型本质上等同于WS小世界模型。 (NW constitutive principles of small-world networks: from the rules of a ring network, network with N nodes, each node is connected to the K node with its nearest neighbor K edges, and meet N > > K > > In (N) > > 1. Followed by randomization into the plus side, with probability p with an edge between a pair of nodes in a randomly selected. Wherein between any two different nodes at most only one edge, and each node can not have a side connected with itself. P value can be changed to achieve the transition from the nearest neighbor coupling network (p = 0) coupled to the global network (p = 1). When p is small enough and large enough N, NW small-world model is essentially the same as the WS small-world model.)